Optimisation of a Protocrystalline Hydrogenated Amorphous Silicon Top Solar Cell for Highest Stabilised Efficiency

Optimisation of a protocrystalline hydrogenated amorphous silicon top solar cell for highest stabilised efficiency

Jimmy Melskens

Cover: A selection of the solar cells discussed in chapter 5 and chapter 6 of this thesis. Photo courtesy of S. M. Klingens.

Optimisation of a protocrystalline

hydrogenated amorphous silicon top

solar cell for highest stabilised efficiency

Jimmy MELSKENS

A thesis written for obtaining the degree of

Master of Science in Electrical Engineering (variant Microelectronics)

from Delft University of Technology

Exam committee: Prof. dr. C. I. M. Beenakker Dr. M. Zeman Dr. M. Bartek Ir. G. van Elzakker Delft, November 2007

Acknowledgements The completion of this M.Sc. thesis project and report would not have been possible without the support of several people.

Firstly, I would like to thank dr. Miro Zeman for writing an interesting project proposal for me, guiding me throughout the whole project, and showing me the possibilities of solar cells in everyday life. In addition to this, I am grateful for the opportunity I was given to publish a part of my work in a paper, of which I have presented the contents at the European Materials Research Society 2007 Spring Meeting in Strasbourg, France.

Secondly, I am grateful for the support of ir. Gijs van Elzakker and ir. Bas Vet who have advised me during the last year to overcome practical difficulties and for all the times they have made free for me to discuss both the theoretical and practical issues I had to deal with. I am particularly grateful for providing me with the samples I required and the support I received during times of tedious measurements. Also, I am grateful for numerous discussions with dr. René van Swaaij on several theoretical and practical issues.

Further, I would like to thank ing. Martijn Tijssen and ing. Kasper Zwetsloot for providing me with the samples I needed for my project and their expertise on the measurement systems in the Solar Cell Group. I am also thankful to Delft ChemTech for making available their spectrophotometer and to dr. Stefan Luxembourg for performing the spectrophotometry measurements I required.

Besides the support I received from the above-mentioned and other members of the Solar Cell Group, I am thankful as well for the assistance of ing. Johan Vijftigschild during the outdoor experiment I performed, and for the craftsmanship of the people in the faculty’s mechanical workshop Dienst Elektronische en Mechanische Ontwikkeling (DEMO), without whom improvement of the Fourier Transform Photocurrent Spectroscopy (FTPS) measurement setup would not have been possible.

Apart from the technical support I received over the last year, I am grateful for the nice atmosphere in the Solar Cell Group in which I have been working. Whenever I needed some distraction from the work, there was always some time to have a chat with someone. In this respect, I would like thank my fellow M.Sc. students in the Solar Cell Group in particular: Yingge Li (China), Angela Thelen (United States of America), and Ahmad Dagamseh (Jordan). Working in such an international community as the Solar Cell Group and the Delft Institute of Microsystems and Nanoelectronics (DIMES) as a whole has been a very pleasant experience.

Last but not least, I would like thank my family and friends for their support during the time I spent in Delft University of Technology to obtain my M.Sc. degree and I hereby apologise for all those times I gave preference to my work in university over social activities.

Abstract In recent decades, the public awareness of the need for renewable energy sources has increased greatly. Considering the current climate changes, it is clear that today’s energy systems have to be radically transformed onto a more sustainable basis to avoid the otherwise very likely adverse effects of global warming on tomorrow’s society and economy. In this framework, solar cells offer an interesting alternative for large-scale electricity generation. The first-generation crystalline silicon (c-Si) solar cells, which still dominate the photovoltaic market, will likely not be used for such large-scale applications, because of the relatively large amounts of material that would be required for the fabrication. Thin- film solar cells, such as hydrogenated amorphous silicon (a-Si:H) solar cells, have a great potential with respect to the costs, because much smaller amounts of material are needed in the fabrication process in comparison to c-Si solar cells. However, the typical conversion efficiency of an a-Si:H silicon solar cell is much lower than the typical conversion efficiency of a c-Si solar cell. Further, the performance of an a-Si:H solar cell degrades over time when the solar cell is exposed to light, which is not the case for c-Si solar cells. In an attempt to increase the conversion efficiency of thin-film solar cells, research interest moved towards multiple-junction solar cells, as opposed to the conventional single-junction solar cells, so a wider range of the solar spectrum could be absorbed. One particularly interesting multiple-junction solar cell is the so-called micromorph tandem solar cell, which consists of an a-Si:H top solar cell and a hydrogenated microcrystalline silicon (μc-Si:H) bottom solar cell. The interesting aspect of this particular multiple-junction solar cell is that both the bottom and the top solar cell can be produced from the same cheap base material: silicon. Both solar cells can be deposited by means of plasma-enhanced chemical vapour deposition (PECVD) from silane gas. To obtain a highly efficient a-Si:H solar cell for possible later use in a micromorph tandem solar cell, it will be attempted in this thesis to optimise the heart of the a-Si:H solar cell: the absorber layer. To obtain a stable material, a hydrogen-to-silane dilution ratio of 20 is used during the PECVD deposition of a-Si:H. The influence of various deposition parameters, such as the pressure, the rf-power, the silane flow, and the substrate temperature on the quality of films and absorber layers is investigated. Fourier Transform Photocurrent Spectroscopy is used to evaluate the quality of Si:H films and solar cell absorber layers, since from the obtained sub-band gap absorption coefficient spectrum the defect concentration can be estimated. It is found that the highest material quality of films and absorber layers is achieved for a high deposition pressure, a low rf-power, and a low substrate temperature. The silane flow does not have a significant influence of the quality of the deposited material. None of these deposition parameters has an influence on the degradation rate in films and absorber layers. An increased stability against light soaking is observed for the films and absorber layers deposited at a hydrogen-to-silane dilution ratio of 20 in comparison to a film and an absorber layer deposited from undiluted silane.

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The Stone Age did not end for lack of stone, and the Oil Age will end long before the world runs out of oil.

-- Sheikh Ahmed Zaki Yamani, Saudi Arabia's Minister of Oil and Mineral Resources from 1962 until 1986.

Quoted by The Economist, October 23, 2003.

Contents

Acknowledgements ...... v

Abstract...... vii

List of figures ...... xi

List of tables...... xxi

Abbreviations ...... xxiii

1 Introduction...... 1

1.1 CONTEXT AND PROBLEM STATEMENT...... 1 1.2 OUTLINE...... 2

2 The importance of thin-film amorphous silicon solar cells ...... 5

2.1 CLIMATE CHANGE...... 5 2.1.1 Historical overview and recent findings...... 5 2.1.2 Kyoto Protocol ...... 10 2.2 THE GLOBAL ENERGY MARKET...... 12 2.2.1 Energy resources and consumption ...... 12 2.2.2 The need for renewable energy ...... 14 2.2.3 The importance of photovoltaic technology...... 19 2.3 OVERVIEW OF THE PHOTOVOLTAIC INDUSTRY ...... 20 2.3.1 Historical technological overview ...... 20 2.3.2 The recent growth of the photovoltaic industry ...... 23 2.4 DEVELOPMENTS IN THIN-FILM AMORPHOUS SILICON SOLAR CELLS ...... 25 2.5 FUTURE DEVELOPMENTS IN THIN-FILM SOLAR CELLS ...... 26 2.5.1 Renewable energy policy developments...... 26 2.5.2 Technological developments ...... 27

3 The properties of amorphous silicon ...... 31

3.1 HISTORICAL OVERVIEW...... 31 3.2 THE DIFFERENT TYPES OF SILICON ...... 32 3.3 MATERIAL PARAMETERS OF HYDROGENATED AMORPHOUS SILICON ...... 34 3.3.1 Density of states distribution...... 34 3.3.2 Absorption coefficient spectrum...... 37 3.3.3 Optical band gap ...... 39 3.4 PHOTO-INDUCED DEGRADATION: STAEBLER-WRONSKI EFFECT ...... 40 3.5 HYDROGENATED AMORPHOUS SILICON SOLAR CELLS...... 43 3.5.1 Solar cell structures...... 43 3.5.2 Deposition techniques ...... 45 3.5.3 External parameters ...... 47

4 Measuring the absorption coefficient spectrum ...... 49

4.1 REFLECTION / TRANSMISSION...... 49 4.2 PHOTOTHERMAL DEFLECTION SPECTROSCOPY ...... 51

4.3 CONSTANT PHOTOCURRENT METHOD ...... 52 4.4 DUAL BEAM PHOTOCONDUCTIVITY...... 54 4.5 FOURIER TRANSFORM PHOTOCURRENT SPECTROSCOPY ...... 55 4.5.1 Theory...... 55 4.5.2 Experimental setup...... 58 4.5.3 Improved experimental setup ...... 61 4.6 CALCULATING THE ABSORPTION COEFFICIENT SPECTRUM...... 67 4.7 COMPARISON OF FTPS WITH PDS, CPM, AND DBP...... 69

5 Optimising a-Si:H films and solar cell absorber layers ...... 71

5.1 OPTIMISATION PROCEDURE ...... 71 5.1.1 Introduction ...... 71 5.1.2 Deposition conditions of films and solar cells ...... 72 5.2 VARIATION OF THE DEPOSITION PRESSURE ...... 75 5.3 VARIATION OF THE RF-POWER...... 87 5.4 VARIATION OF THE SILANE FLOW...... 91 5.5 VARIATION OF THE DEPOSITION TEMPERATURE ...... 95

6 Photo-induced degradation of a-Si:H films and solar cells ..... 99

6.1 EXPERIMENTAL DETAILS ...... 99 6.2 DEGRADATION OF THE PRESSURE SERIES...... 99 6.3 DEGRADATION OF THE RF-POWER SERIES ...... 106 6.4 DEGRADATION OF THE SILANE FLOW SERIES ...... 111 6.5 DEGRADATION OF THE SUBSTRATE TEMPERATURE SERIES ...... 115

6.6 DEGRADATION OF THE JSC AFTER STABILISATION OF THE FF ...... 119 6.7 OUTDOOR EXPERIMENT ...... 122

7 Conclusions and recommendations ...... 127

7.1 CONCLUSIONS ...... 127 7.2 RECOMMENDATIONS FOR FUTURE WORK ...... 127

References ...... 129

Appendices ...... 135

APPENDIX A: MATLAB SCRIPT USED FOR PROCESSING FTPS DATA...... 135

List of figures Figure 2.1 Atmospheric concentrations of carbon dioxide, 7 methane and nitrous oxide over the last 10,000 years. Measurements are shown from atmospheric samples (red lines) and ice cores (other lines). The corresponding radiative forcings are shown on the right hand axes. Radiative forcing is the change in net irradiance at the tropopause due to changes in GHG concentrations after allowing for stratospheric temperatures to readjust to radiative equilibrium, but with surface and tropospheric temperatures held fixed at the unperturbed values. These graphs are taken from [4].

Figure 2.2 Observed changes in (a) global average surface 8 temperature, (b) global average sea level from tide gauge (blue) and satellite (red) data, and (c) Northern Hemisphere snow cover for March – April. Uncertainties and yearly averages are depicted as shaded areas and circles. All changes are relative to corresponding averages for the period 1961 – 1990. These graphs are taken from [4].

Figure 2.3 Multi-model global averages of surface warming 9 (relative to 1980 – 1999) shown as continuations of the 20th century simulations for the different SRES scenarios (A1: rapid economic growth, global population peaking mid-21st century, thereafter declining, rapid introduction of new and more efficient technologies, convergent world; A1FI: fossil fuel intensive energy market; A1B: balanced energy market; A1T: predominantly non-fossil fuel market; A2: heterogeneous world with continuous population growth, slower and more fragmented technological changes; B1: economic and global population growth as in A1, but with an emphasis on global solutions to economic, social and environmental stability; B2: continuous economic and population growth, but slower than in A2 and with an emphasis on local solutions to economic, social and environmental stability, less rapid and more fragmented technological change than in B1 and A1). Shading denotes the ±1 standard deviation range of individual model annual averages. The orange line is for the experiment where concentrations were held constant at year 2000 values. The grey bars on the right indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES scenarios. This graph is taken from [4].

Figure 2.4 Estimation of (a) energy resources and (b) power 13 consumption in 2004 subdivided in the different types of energy sources. Graph (a) is taken from [27] and originally from [28]; graph (b) is created from [25] and [26].

Figure 2.5 World marketed energy consumption as projected 16 by the EIA’s BAU scenario. 1 Quadrillion Btu (= British thermal unit) corresponds to 1.055 EJ. Graph is taken from [24].

Figure 2.6 World marketed energy use by fuel type as 16 projected by the EIA’s BAU scenario. Liquids in this graph are referring to oil. Graph is taken from [24].

Figure 2.7 World electricity generation by fuel type. The BAU 17 scenario identifies coal as the future’s most important resource for satisfying the global energy demand. Graph is taken from [24].

Figure 2.8 Global savings in CO2 emissions in the IEA’s 17 alternative scenario compared to the reference scenario. Graph is taken from [38].

Figure 2.9 Transforming the global energy mix: the exemplary 18 path until 2050 and 2100 according to the WBGU. Graph is taken from [27], but is originally from [39].

Figure 2.10 Development of global electricity generation under 19 the IEA reference scenario (above) and the Greenpeace / EREC alternative scenario (below). Graph is taken from [40].

Figure 2.11 Changes of cell technology shares in the PV market 22 (a) since 1980 and (b) since 1999. In these graphs, Cz (Czochralski, the process used for producing monocrystalline Si) is equivalent to mono c-Si, Px (polycrystalline Si) is equivalent to multi c-Si, and thin film refers to CdTe, a-Si, and CIS together. Other thin-film Si-based technologies have been included in the a-Si figure, since their market share is very small. Even though the market share of thin-film PV is currently rising again (mostly due to CdTe), the market is still largely dominated by wafer-based first-generation solar cells. Graph (a) is taken from [56]; graph (b) is taken from [55].

Figure 2.12 Production numbers of the top 10 cell producers 24 and the market shares per region in 2006 and 2005. China’s market share has clearly increased very heavily in one year, threatening the leading position of Japan. Graph is taken from [55].

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Figure 3.1 Schematic representation of the atomic structure of 32 (a) c-Si, (b) μc-Si:H, and (c) a-Si:H. In c-Si, all Si atoms are covalently bonded to four other Si atoms. Graph is taken from [57].

Figure 3.2 The hydrogen dilution of silane during PECVD 33 deposition of Si:H films induces a phase change from pc-Si:H to mixed (a+ μc)-Si:H and finally to μc-Si:H when the film is grown to a sufficient thickness. Graph is taken from [76].

Figure 3.3 Bright field electron micrographs of Si:H layers of 34 an equal thickness (~1 μm) deposited on glass with different hydrogen dilution ratios R. As illustrated in figure 3.2, the crystalline fraction of the film increases for an increasing value of R while the thickness is kept constant. Graph is taken from [77].

Figure 3.4 Schematic comparison of the densities of electronic 35 states distributions of (a) c-Si and (b) a-Si:H. In c- Si, a clear band gap of 1.1 eV can be identified. In a-Si:H, it is only possible to define a mobility band gap, which is approximately 1.8 eV. Graph is taken from [57].

Figure 3.5 Standard schematic representation of the density of 36 states distribution in a-Si:H with two Gaussian distributions modelling the differently charged defect states. The energy difference denoted as U is known as the correlation energy, which is assumed to be constant. Graph is taken from [61].

Figure 3.6 Typical absorption coefficient spectra and 38 corresponding penetration depth spectra of c-Si, μc-Si:H, and a-Si:H device-quality layers on glass. The red line is the Urbach line, which is used to

calculate the Urbach energy EU. The red shaded area refers to the absorption that is due to defect states in the middle of the band gap. This graph is adapted from [80].

Figure 3.7 The different band gaps of c-Si, μc-Si:H, and a-Si:H 40 cause different regions of the solar spectrum to be absorbed by each material. This graph is adapted from [84].

Figure 3.8 Atomic configuration of a-Si:H (a) before 41 illumination and (b) after illumination. Graph is adapted from [91].

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Figure 3.9 Two examples of possible atomic configurations of a 42 metastable complex of two Si-H bonds in the continuous random network. Note that the two DBs that are stabilised by the metastable complex are not depicted in the figures. Graph is taken from [91].

Figure 3.10 General structure of (a) a c-Si solar cell and (b) an 44 a-Si:H solar cell. The yellow arrows indicate the direction of the incident light. Graph is taken from [57].

Figure 3.11 Schematic representation of an rf-PECVD deposition 46 system. Graph is adapted from [57].

Figure 3.12 Typical J-V curve of an illuminated solar cell 47 including several characteristic values. Graph is adapted from [57].

Figure 4.1 Schematic drawing of the Michelson interferometer, 55 which is the main component of the Thermo Electron Nicolet 5700 FTIR spectrometer.

Figure 4.2 The FTPS measurement setup used throughout this 59 work.

Figure 4.3 Configuration of the mirror and the sample holder 62 on the inside of the hardboard black box in the original FTPS system.

Figure 4.4 Configuration of the mirror and the sample holder 63 on the inside of the aluminium box in the improved FTPS system. The voltage source is not visible in the picture because it is placed under the table on which the system is resting to keep a safe distance between the voltage source and the current amplifier.

Figure 4.5 (a) Typical reflectance spectra for Al and Ag (graphs 65 taken from [109]) and (b) for Al normalised to Ag as obtained from FTPS measurements on a μc-Si:H sample supplied by the University of Neuchâtel.

Figure 4.6 Projection of the modulated light onto the new 66 sample holder when using (a) an elliptically concave mirror, (b) a parabolic off-axis mirror, (c) a parabolic off-axis mirror in combination with a slit. All three pictures are depicted on the same scale. The diameter of the circular hole in the sample holder over which a sample is placed is 20 mm.

Figure 4.7 Absorption coefficient spectra obtained from FTPS 67 on a μc-Si:H solar cell with and without using a slit that prevents the secondary light spots from illuminating the sample.

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Figure 5.1 The typical structure of (a) the individual films on 74 glass and (b) the p-i-n solar cells that are investigated in this report. Note that the buffer layer is not depicted in the p-i-n structure. Graphs are adapted from [57].

Figure 5.2 Absorption coefficient spectra obtained from FTPS 75 and RT on silicon films deposited at R = 20 and varying pressures.

Figure 5.3 Absorption coefficient spectra obtained from DBP 76 and RT on silicon films deposited at R = 20 and varying pressures. The investigated films are equal to the films of which the absorption coefficient spectra are depicted in figure 5.2.

Figure 5.4 Absorption coefficient spectra obtained from 77 FTPS / RT on the solar cells with absorber layers deposited at R = 20 and varying pressures corresponding to the aforementioned films on glass.

Figure 5.5 Absorption coefficient spectra obtained from 78 DBP / RT and FTPS / RT on silicon films deposited at R = 20 and pressures of 1.35 mbar and 2.40 mbar and the absorption coefficient spectra obtained from FTPS / RT on the corresponding solar cells.

Figure 5.6 Transmittance curves of the structures through 79 which the light passes before the layer of interest in an FTPS measurement is illuminated. In a film, this substrate is just Corning, whereas in a solar cell, the light has to pass through an Asahi / p / buffer structure before the light reaches the i-layer.

Figure 5.7 α1.2 eV and Nd as a function of deposition pressure of 81 films and corresponding solar cell absorber layers deposited at R = 20 obtained from FTPS / RT and DBP / RT. The values obtained from DBP / RT and FTPS / RT on the films match very well which

confirms the accuracy of FTPS. Note that the α1.2 eV values of the films deposited at pressures below

2.00 mbar do not directly correspond to Nd values via the proportionality factor of 5×1016 cm-2, as these films are not fully amorphous.

Figure 5.8 Defect density as a function of deposition pressure 82 of films and corresponding solar cell absorber layers

obtained from the α spectrum using the α1.2 eV estimation and the integration method. Since the films deposited at pressures below 2.00 mbar are not fully amorphous, these films are not further considered in the comparison of the two methods used for estimating the defect density.

Figure 5.9 E04, ET, EK, and EU as a function of deposition 83 pressure of films and corresponding solar cell absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of

films and absorber layers deposited at R = 20, E04, ET, EK, and EU of a reference film and absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 5.10 The external parameters Voc, Jsc, FF, and η as a 85 function of deposition pressure of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs. Note that the solar cell with the R = 0 absorber layer and the solar cell with the R = 20 absorber layer deposited at 2.00 mbar have been deposited with both an Al and an AgAl back contact.

Figure 5.11 Absorption coefficient spectra obtained from 88 FTPS / RT on silicon films and corresponding solar cell absorber layers deposited at R = 20 and varying rf-powers.

Figure 5.12 Defect density as a function of rf-power of films and 88 corresponding solar cell absorber layers obtained from their α spectra.

Figure 5.13 E04, ET, EK, and EU as a function of rf-power of films 89 and corresponding solar cell absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and absorber

layers deposited at R = 20, E04, ET, EK, and EU of a reference film and an absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 5.14 The external parameters Voc, Jsc, FF, and η as a 90 function of rf-power of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 5.15 Absorption coefficient spectra obtained from 92 FTPS / RT on silicon films and corresponding solar cell absorber layers deposited at R = 20 and varying silane flows.

Figure 5.16 Defect density as a function of silane flow of films 93 and corresponding solar cell absorber layers obtained from their α spectra.

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Figure 5.17 E04, ET, EK, and EU as a function of silane flow of 93 films and corresponding solar cell absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and absorber

layers deposited at R = 20, E04, ET, EK, and EU of a reference film and an absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 5.18 The external parameters Voc, Jsc, FF, and η as a 94 function of silane flow of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 5.19 Absorption coefficient spectra obtained from 96 FTPS / RT on silicon films and corresponding solar cell absorber layers deposited at R = 20 and varying substrate temperatures.

Figure 5.20 Defect density as a function of substrate 97 temperature of films and corresponding absorber layers obtained from their α spectra.

Figure 5.21 E04, ET, EK, and EU as a function of substrate 97 temperature of films and corresponding absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and

absorber layers deposited at R = 20, E04, ET, EK, and EU of a reference film and an absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 5.22 The external parameters Voc, Jsc, FF, and η as a 98 function of substrate temperature of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs.

Figure 6.1 Absorption coefficient spectra obtained from FTPS 100 on silicon films deposited at R = 20 and pressures of 1.35 mbar and 2.60 mbar at three different moments during the light soaking experiment: initial, after 1.3 hours, and after 173 hours.

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Figure 6.2 Defect density as a function of deposition pressure 101 of films and corresponding solar cell absorber layers obtained from their α spectra using the integration method at three different moments during the light soaking experiment. Since the films deposited at pressures below 2.00 mbar are not fully

amorphous, their Nd values are not further considered and therefore they have been omitted from the graph.

Figure 6.3 Evolution in time of the external parameters of the 103 solar cells with the R = 20 absorber layers deposited at different pressures and the reference solar cells with the R = 0 absorber layer. All external parameters are normalised to their initial values.

Figure 6.4 External parameters of the solar cells with the 105 R = 20 absorber layers deposited at different pressures and the reference solar cells with the R = 0 absorber layer as a function of the deposition pressure at three different moments during the light soaking experiment.

Figure 6.5 Defect density as a function of rf-power of films and 107 corresponding solar cell absorber layers obtained from their α spectra at three different moments during the light soaking experiment.

Figure 6.6 Evolution in time of the external parameters of the 109 solar cells with the R = 20 absorber layers deposited at different rf-powers and the reference solar cell with the R = 0 absorber layer. All external parameters are normalised to their initial values.

Figure 6.7 External parameters of the solar cells with the 110 R = 20 absorber layers deposited at different rf- powers and the reference solar cell with the R = 0 absorber layer as a function of the rf-power at three different moments during the light soaking experiment.

Figure 6.8 Defect density as a function of silane flow of films 112 and corresponding solar cell absorber layers obtained from their α spectra at three different moments during the light soaking experiment.

Figure 6.9 Evolution in time of the external parameters of the 113 solar cells with the R = 20 absorber layers deposited at different silane flows and the reference solar cell with the R = 0 absorber layer. All external parameters are normalised to their initial values.

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Figure 6.10 External parameters of the solar cells with the 114 R = 20 absorber layers deposited at different silane flows and the reference solar cell with the R = 0 absorber layer as a function of the silane flow at three different moments during the light soaking experiment.

Figure 6.11 Defect density as a function of substrate 116 temperature of films and corresponding solar cell absorber layers obtained from their α spectra at three different moments during the light soaking experiment.

Figure 6.12 Evolution in time of the external parameters of the 117 solar cells with the R = 20 absorber layers deposited at different substrate temperatures and the reference solar cell with the R = 0 absorber layer. All external parameters are normalised to their initial values.

Figure 6.13 External parameters of the solar cells with the 118 R = 20 absorber layers deposited at different substrate temperatures and the reference solar cell with the R = 0 absorber layer as a function of the substrate temperature at three different moments during the light soaking experiment.

Figure 6.14 Reflectance spectra of four different configurations 121 of the back part of a solar cell at four different moments during the light soaking and annealing experiments. Note that only for the samples with an Al layer, an extra annealing step of 30 minutes at 130 °C has been performed at the start of these experiments, since this also has been done for the solar cells with an Al back contact.

Figure 6.15 Evolution in time of the external parameters of a 123 solar cell with an R = 20 absorber layer and a solar cell with an R = 0 absorber layer during both the outdoor experiment and the indoor experiment. In this context, “indoor” refers to the light soaking experiment discussed in the previous sections of this chapter. All external parameters are normalised to their initial values. Note that each integer value on the time axis corresponds to midnight.

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Figure 6.16 Temperature and irradiance variations during the 124 outdoor experiment. The irradiance values have been obtained from measurements with a pyranometer. Note that the temperature values depicted here do not correspond to the ambient temperature, but to the temperature on the back side of some crystalline module located next to the plastic box containing the R = 0 and R = 20 solar cells. It has been verified that the temperature inside the plastic box is comparable to the temperature on the back side of the module.

List of tables Table 2.1 Current status of the different solar cell 23 technologies in terms of conversion efficiency. Expensive technologies that serve a niche market, such as GaAs, have been omitted from this table, since they form a negligible fraction of the total PV market. Thin-film technologies show lower conversion efficiencies than c-Si, but this does not phase out second-generation technology in favour of c-Si, because of the lower cost per area. Table data are taken from [57].

Table 5.1 Deposition conditions used for depositing the 73 different layers of the investigated solar cells by means of rf-PECVD. The deposition conditions of the individual films on glass are equal to the conditions that are used for the deposition of the i- layers in the solar cells.

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Abbreviations α absorption coefficient (spectrum)

α1.2 eV absorption coefficient at 1.2 eV δ retardation

δmax ` maximum retardation δmin minimum retardation η conversion efficiency ηg generation quantum efficiency λ (photon) wavelength μ (charge carrier) mobility μc-Si microcrystalline silicon μc-Si:H hydrogenated microcrystalline silicon μm micrometre ν wavenumber σph photoconductivity τ (charge carrier) lifetime υ scan velocity of the movable mirror (in an interferometer) ϕ phase difference Δν difference in wavenumber between two samples (in an interferometer) Δn concentration of photo-generated electrons Φ0 incident photon flux density (a+ μc)-Si:H hydrogenated mixed-phase silicon A absorbance AC alternating current A/D analogue-to-digital Ag silver Al aluminium AM1.5 optical air mass 1.5 APPCDC Asia-Pacific Partnership on Clean Development and Climate AP6 see APPCDC AR4 Fourth Assessment Report (of the UN IPCC) a-Si amorphous silicon a-Si:H hydrogenated amorphous silicon a-SiC:H hydrogenated amorphous silicon carbide a-SiGe:H hydrogenated amorphous silicon germanium Au gold B boron or intensity of a light source modified by instrumental and environmental characteristics (in an interferometer)

B2H6 diborane BAU business-as-usual BP British Petroleum Btu British thermal unit (= 1,055 Joule) c velocity of light in vacuum C carbon or coulomb CaF2 calcium fluoride CCPM energy-independent constant (in CPM)

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Cd cadmium CdS cadmium sulphide CdTe cadmium telluride CH4 methane CIS see CuInSe2 CIGS see CuInGaSe2 CO2 carbon dioxide CPM Constant Photocurrent Method c-Si crystalline silicon Cu copper

Cu2O copper oxide CuInGaSe2 copper indium gallium diselenide CuInSe2 copper indium diselenide d penetration depth (spectrum) or thickness (of a film) D+ positively charged dangling bond D- negatively charged dangling bond D0 neutral dangling bond DB dangling bond DBP Dual Beam Photoconductivity DC direct current DOS density of states DPM Defect-Pool Model DTGS deuterated triglycerine sulphate E (photon) energy 4 -1 E04 energy level corresponding to α = 10 cm EC conduction band edge (in c-Si) or conduction band mobility edge (in a-Si:H)

EF Fermi level Eg band gap (in c-Si) or mobility band gap (in a-Si:H) EIA Energy Information Administration EJ etajoule (1018 Joule)

Emob mobility band gap Eopt optical band gap EREC European Renewable Energy Council ESR Electron Spin Resonance

ET Tauc gap EU European Union

EU Urbach energy eV electronvolt

EV valence band edge (in c-Si) or valence band mobility edge (in a-Si:H) fν modulation frequency of the light with wavenumber ν (in an interferometer) FF fill factor FTIR Fourier Transform Infrared (spectrometer) FTPS Fourier Transform Photocurrent Spectroscopy G light intensity or optical generation rate of electrons GaAs gallium arsenide GDP gross domestic product Ge germanium GGAS Greenhouse Gas Abatement Scheme GW gigawatt

xxiv h Planck’s constant H hydrogen (atomic)

H2 hydrogen (molecular) HeNe helium-neon Hz Hertz i imaginary unit I intensity of the output beam (in an interferometer) IAEA International Atomic Energy Agency IEA International Energy Agency IPCC Intergovernmental Panel on Climate Change Iph photocurrent

Is intensity of a light source (in an interferometer) J current density Jmpp maximum power point current density J·s Joule-second

Jsc short-circuit current density k extinction coefficient kW kilowatt KBr potassium bromide l length of electrodes (in a photoconductivity measurement) Lamb ambipolar diffusion length lb pound (= 453.59237 gram) meV millielectronvolt mm millimetre MW megawatt n (real) refractive index ñ complex refractive index N nitrogen

N2O nitrous oxide nc-Si nanocrystalline silicon nc-Si:H hydrogenated nanocrystalline silicon

Nd defect density Ni nickel nm nanometre NREL National Renewable Energy Laboratory NSW New South Wales O oxygen OECD Organisation for Economic Co-operation and Development p constant describing the shape of the DOS distribution in the extended states of the conduction band (in a- Si:H) P phosphorus

Pb2S lead sulphide pc-Si:H hydrogenated protocrystalline silicon PDS Photothermal Deflection Spectroscopy PECVD plasma-enhanced chemical vapour deposition

PH3 phosphine Pmpp generated maximum power poly-Si polycrystalline silicon poly-Si:H hydrogenated polycrystalline silicon

xxv ppb parts per billion (= 1,000 million) ppm parts per million Pt platinum PV photovoltaic (systems / technology / industry) q constant describing the shape of the DOS distribution in the extended states of the valence band (in a-Si:H) or the charge of an electron rf radio-frequency R hydrogen-to-silane dilution ratio or reflectance REN21 Renewable Energy Policy Network for the 21st Century RGGI Regional Greenhouse Gas Initiative RT Reflection / Transmission Se selenium Si silicon SiH2 silylene SiH3 silyl SiH4 silane SiO2 quartz SJT Stutzmann-Jackson-Tsai SnO2 tin oxide SO2 sulphur dioxide SRES Special Report on Emission Scenarios SWE Staebler-Wronski effect t time T transmittance TAR Third Assessment Report (of the UN IPCC) TCO transparent conductive oxide Te tellurium TEM Transmission Electron Microscopy TF thin-film Tl2S thallium sulphide U correlation energy or applied voltage (in a photoconductivity measurement) UN United Nations UNEP United Nations Environment Programme UNFCCC United Nations Framework Convention on Climate Change UNSD United Nations Statistics Division V voltage VLS-PV very large scale photovoltaic (systems / technology / industry) Vmpp maximum power point voltage

Voc open-circuit voltage w distance between measuring electrodes (in a photoconductivity measurement) WBGU Wissenschaftlicher Beirat der Bundesregierung Globale Umweltveränderungen (German Advisory Council on Global Change) WEC World Energy Council WMO World Meteorological Organization YJ yottajoule (1024 Joule) ZJ zettajoule (1021 Joule)

xxvi

Zn zinc ZnO zinc oxide

xxvii

1 Introduction In this chapter, an introduction to this report is presented. Firstly, in section 1.1, the context in which this M.Sc. project has been performed and the problem statement are explained. Thereafter, in section 1.2, an outline of the report is presented.

1.1 Context and problem statement Hydrogenated amorphous silicon (a-Si:H) is a conventional photovoltaic (PV) material that is used in the active part of a solar cell, the absorber layer. For a long time, however, a-Si:H solar cells could not commercially compete with the solar cells that as of today still dominate the PV market: crystalline silicon (c-Si) solar cells. This is mainly caused by the fact that the conversion efficiencies of a-Si:H solar cells are lower than the conversion efficiencies of c-Si solar cells. Additionally, the performance of a-Si:H solar cells degrades when they are exposed to light (this is known as the Staebler-Wronski effect), which is not the case for c-Si solar cells. The main advantage that a-Si:H solar cells offer over c-Si solar cells is the strongly reduced amount of silicon that is required for a-Si:H solar cells, which makes a-Si:H an interesting material for fabricating low-cost solar cells. For a long time, this advantage did not outweigh the disadvantages of a-Si:H, which limited its application to off-grid applications that had to be cheap and did not require a high conversion efficiency, such as solar- powered wrist watches and hand calculators. Moreover, early a-Si:H modules suffered from a bad reputation for their short lifetime, caused by e.g. encapsulation problems. The reliability problems were gradually solved, but the interest in a-Si:H solar cells for large-scale applications remained low in comparison to c-Si solar cells, mainly due to the lower efficiency of a-Si:H solar cells. This situation changed in 1994 after the introduction of the so-called “micromorph” tandem solar cell, which contains a top absorber layer of a-Si:H and a bottom absorber layer of hydrogenated microcrystalline silicon (μc-Si:H). Because of the use of two absorber layers, a wider range of the solar spectrum can be absorbed, which leads to an increase of the conversion efficiency of the solar cell. Before the introduction of μc-Si:H, the bottom absorber layer was usually made from hydrogenated amorphous silicon germanium (a-SiGe:H). Since this required the use of expensive germanium, an a-Si:H/a-SiGe:H tandem solar cell could not be produced in a cost-effective way. However, μc-Si:H could now be used instead of a-SiGe:H, and since both a-Si:H and μc-Si:H can be produced at a relatively low price, a-Si:H has become an interesting photovoltaic material for large-scale PV applications that has the potential to compete with the established c-Si solar cells. Further, these materials can be deposited at relatively low temperatures (less than 200 °C), which enables the use of cheap flexible plastic substrate for the deposition of the solar cell. This is why a-Si:H technology offers an interesting possibility for large-scale electricity generation in a renewable manner. Although large improvements in the development of a-Si:H technology have been made thus far, the market share of solar cells based on a-Si:H is currently still below 10%. Mainly, this is due to the fact that the machinery that is

1 required to produce a-Si:H based modules on a commercial scale has only become available recently. Secondly, the biggest problem with a-Si:H is still not solved: the Staebler-Wronski effect. In the framework of this latter problem, it is attempted in this thesis to optimise an a-Si:H solar cell absorber layer for possible future use in a top cell of a micromorph solar cell. The optimisation is performed by investigating the variation of several parameters that are used for the deposition of the absorber layer by means of radio-frequency plasma- enhanced chemical vapour deposition (rf-PECVD) in a structured way. To investigate the quality of the deposited material, several deposition parameters are varied while keeping the others constant. For each set of deposition parameters, an individual film on glass and an absorber layer in a solar cell are deposited. Several material properties are then deduced for each sample by means of measurements, so an optimal value for each of the varied deposition parameters can be found. The majority of these material properties, such as the defect density, can be deduced from the absorption coefficient spectrum. The defect density is of great importance in order to judge the suitability of the material for making good electronic devices. As the defect density can be estimated from the sub-band gap absorption coefficient spectrum, it is important that the absorption coefficient is accurately determined for the sub-band gap photon energy range. A novel method that can be used for this purpose is Fourier Transform Photocurrent Spectroscopy (FTPS). To further optimise the deposition parameters, the evolution in time during light soaking of e.g. the defect density has to be monitored for all films and solar absorber layers, since this is directly related to the Staebler-Wronski effect. The quality of all films and absorber layers is again investigated during this light soaking experiment by means of FTPS and some other measurement techniques that will not be discussed here. Finally, the optimisation procedure can be completed when the quality of the samples is considered again after light soaking.

1.2 Outline The outline of this report is as follows. In the second chapter of this report, the importance of thin-film amorphous silicon solar cells is explained in the broader context of e.g. climate change, the global energy market, the need for renewable energy, and recent developments in thin- film amorphous silicon solar cells. This chapter is mainly interesting for readers who are not familiar with the field of solar cells, as it is full of background information. It is however not required for understanding the core of this thesis: the optimisation of the deposition parameters of an a-Si:H solar cell absorber layer. Thereafter, in chapter 3, the properties of amorphous silicon and the theory that is required for understanding the results of the optimisation procedure will be discussed. Since a large part of the optimisation procedure is based on material parameters that are derived from the absorption coefficient spectrum, chapter 4 covers several measurement methods that can be used to obtain it. In that chapter, extra attention will be paid to FTPS, since it is a very frequently used measurement method in the optimisation of the deposition parameters of the absorber layer. The optimisation procedure is explained in chapter 5,

2 which also includes the results from the optimisation procedure. In chapter 6, the optimisation procedure is continued by light soaking all previously discussed films and absorber layers and performing the optimisation procedure again. The final conclusions are then included in chapter 7, which also contains the recommendations for future work.

2 The importance of thin-film amorphous silicon solar cells This chapter describes the importance of thin-film amorphous silicon solar cells. To be able to place the research on renewable energy in a broader context, the first section of this chapter contains a discussion on the matter of climate change. Thereafter, an overview of the energy market is given, which is followed by an explanation of the need for renewable energy in section 2.2. In section 2.3, an overview of the photovoltaic industry is given, which is followed by the recent developments in thin- film amorphous silicon solar cells in section 2.4. Finally, in section 2.5, an outlook on the future developments in thin-film solar cells is given.

2.1 Climate change

2.1.1 Historical overview and recent findings Since the First World Climate Conference in Geneva, Switzerland in 1979, a still growing amount of scientific research is spent on a nowadays well- known phenomenon: climate change. This conference, sponsored by the World Meteorological Organization (WMO), was the first to identify global warming as a serious problem and was the first to attribute this warming effect to increased concentrations of carbon dioxide in the Earth’s atmosphere from the burning of fossil fuels, deforestation and changes in land use [1]. Throughout the 1980s, the scientific community organised more and more international meetings, as both evidence and concern about climate change were growing. This led to the establishment of the Intergovernmental Panel on Climate Change (IPCC) by the WMO and the United Nations Environment Programme (UNEP) in 1988, aiming for increased understanding of climate change, its potential impacts and options for adaptation and mitigation [2]. Between 1990 and 2007, the IPCC has published four landmark reports which attempt to quantify the climate change in facts and figures. The differences between the reports lie mostly in an increased scientific consensus for the latter editions (the only scientific organisation that does not recognise the predominant opinion is the American Association of Petroleum Geologists [3]) and a decreased uncertainty in the projections for future greenhouse gas (GHG) emissions and global warming, considering different scenarios for GHG emission mitigation, global warming, use of fossil fuels and population growth. The most recent of the four, the Fourth Assessment Report (AR4), could be summarised in the following striking statements [4]:

• Warming of the climate system is unequivocal. • Most of the observed increase in globally averaged temperatures since the mid-20th century is very likely (> 90% certain) due to the observed increase in anthropogenic GHG concentrations.

• The levels of the GHGs carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) have increased markedly as a result of human activities since 1750 and now far exceed pre-industrial values and the natural range of the last 650,000 years (see figure 2.1): the

CO2 concentration as of 2005 was 379 ppm (natural range: 180 ppm – 300 ppm), the CH4 concentration was 1774 ppb (natural range: 320 ppb – 790 ppb) and the N2O concentration reached up to 319 ppb (pre-industrial level: 270 ppb). • The main sources of the increase in GHG levels are fossil fuel use (CO2 and CH4) and human agricultural activity (N2O and CH4). • Over the last 100 years, the global average temperature has increased approximately by 0.74 °C and 11 of the 12 years between 1995 and 2006 rank among the 12 warmest years since 1850 (see figure 2.2). • Over the past 100 years, the average Arctic temperatures increased at almost twice the global average rate. • The oceans have absorbed more than 80% of the additional heat contained in the climate system since 1961, causing ocean temperatures to rise to depths of at least 3000 m. • Global warming would likely (> 66% certain) have been worse if not for the cooling effects of volcanic and anthropogenic aerosols. • Melting ice masses (Greenland and Antarctica) have very likely (> 90% certain) contributed to the sea level rise between 1993 and 2003. • Snow and ice coverage have decreased on average in both the Northern and Southern Hemisphere (see figure 2.2). • Sea levels have risen at an average rate of 1.8 mm/year between 1961 and 2003 and at an average rate of 3.1 mm/year between 1993 and 2003 (see figure 2.2).

The above-listed summary of conclusions is far from complete. All four IPCC reports are very extensive and including all major conclusions and observations here would be too much of a digression from the following sections and chapters of this report. Therefore, the interested reader is referred to [5] for more facts, numbers and figures on the observed climate changes and a number of model-based projections for future GHG levels, surface air warming, sea level rise etc. These projections are based on the Special Report on Emissions Scenarios (SRES), which was prepared by the IPCC for the Third Assessment Report (TAR). Some conclusions from the SRES include [6]:

• During the course of the 21st century, the surface air temperature rise will be somewhere in between 1.4 °C (1.1 °C – 2.9 °C) for scenario B1 and 4.0 °C (2.4 °C – 6.4 °C) for scenario A1FI (see figure 2.3). A rise of more than 2 °C is considered to be intolerable. • In the next two decades, a temperature rise of 0.2 °C is expected for all scenarios; this short-term prediction is being confirmed by past model projections and actual observed temperature increases (see figure 2.3). • Sea level rise predictions for the 21st century range from 18 cm – 38 cm (scenario B1) to 26 cm – 59 cm (scenario A1FI). • Heat waves and heavy rainfall will very likely (> 90% certain) be more frequent. • The number of areas affected by droughts, the intensity of tropical storms and the occurrence of extreme high tides will likely (> 66% certain) increase.

Figure 2.1: Atmospheric concentrations of carbon dioxide, methane and nitrous oxide over the last 10,000 years. Measurements are shown from atmospheric samples (red lines) and ice cores (other lines). The corresponding radiative forcings are shown on the right hand axes. Radiative forcing is the change in net irradiance at the tropopause due to changes in GHG concentrations after allowing for stratospheric temperatures to readjust to radiative equilibrium, but with surface and tropospheric temperatures held fixed at the unperturbed values. These graphs are taken from [4].

Figure 2.2: Observed changes in (a) global average surface temperature, (b) global average sea level from tide gauge (blue) and satellite (red) data, and (c) Northern Hemisphere snow cover for March – April. Uncertainties and yearly averages are depicted as shaded areas and circles. All changes are relative to corresponding averages for the period 1961 – 1990. These graphs are taken from [4].

Although the above-mentioned observations and conclusions from the AR4 may seem very clear and represent the mainstream scientific assessment of global warming, there is still a minor group of sceptical scientists who disagree with these findings. Arguments used by these scientists include denial of global warming as a whole, doubt on the accuracy of the IPCC’s projections, the opinion that global warming is more likely to have a

Figure 2.3: Multi-model global averages of surface warming (relative to 1980 – 1999) shown as continuations of the 20th century simulations for the different SRES scenarios (A1: rapid economic growth, global population peaking mid-21st century, thereafter declining, rapid introduction of new and more efficient technologies, convergent world; A1FI: fossil fuel intensive energy market; A1B: balanced energy market; A1T: predominantly non-fossil fuel market; A2: heterogeneous world with continuous population growth, slower and more fragmented technological changes; B1: economic and global population growth as in A1, but with an emphasis on global solutions to economic, social and environmental stability; B2: continuous economic and population growth, but slower than in A2 and with an emphasis on local solutions to economic, social and environmental stability, less rapid and more fragmented technological change than in B1 and A1). Shading denotes the ±1 standard deviation range of individual model annual averages. The orange line is for the experiment where concentrations were held constant at year 2000 values. The grey bars on the right indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES scenarios. This graph is taken from [4].

natural cause than a human one or that its cause cannot be explained yet [7]. Albeit not widely supported, these sceptic opinions could be (mis)used by certain lobbyists and politicians who foresee a threat to their personal or national welfare when climate change mitigation measures would be taken. Details on the political discussions about the controversy of global warming will not be discussed further in this section; an extensive overview of the recent political developments on this matter can be found in [8].

2.1.2 Kyoto Protocol Perhaps more well-known to the general audience than the IPCC or the AR4, is a United Nations amendment to the international treaty on climate change: the Kyoto Protocol . This Protocol, drafted by the United Nations Framework Convention on Climate Change (UNFCCC), assigns limitations to GHG emissions to the signatory nations in order to stabilise the atmospheric GHG concentrations at a level that would prevent dangerous anthropogenic interference with the climate system. As of June 6, 2007, a total of 174 countries have signed and ratified the Protocol [9], making it the world’s politically most endorsed document on the mitigation of climate change. In short terms, the Kyoto Protocol classifies each nation as industrialised (Annex I)†, developed and capable of paying cost for developing countries (Annex II, which is a subset of Annex I)‡, or developing (Non-Annex I). Annex I countries are obliged to reduce their GHG emissions, must present annual GHG inventories, and should have reduced their collective GHG emissions by 5.2% with respect to 1990 levels by 2008 – 2012. Every Annex I country that does not meet this commitment has to reduce its GHG emission to this level after all in the second commitment period (after 2012) and is penalised an additional GHG emission reduction obligation. Each Annex I government is free in its means to reach the emission target on a national level, and can invest in projects in Non-Annex I countries that reduce emissions to avoid more expensive emission reductions in their own country. Such investment schemes, of which the Clean Development Mechanism (CDM) is the most well-known, are profitable to the Non-Annex I economies, since these countries have no GHG emission restrictions and can profit from Annex I countries’ investments. Upon the realisation of a GHG emission reduction project, Non-Annex I countries earn Carbon Credit, which can be sold to Annex I countries later on [10]. Even though this trading mechanism and the Kyoto Protocol as a whole have been introduced as a well-intentioned starting point for international political negotiations and cooperation for mitigating global GHG emissions, some critical notes have to be made. Firstly, the rising economies of China and India have been classified as Non-Annex I countries and have therefore no GHG emission restrictions to meet, although they already accounted for 20.6% of the global CO2 emission in 2003 according to the United Nations Statistics Division (UNSD) [11]. Secondly, two industrialised countries which are large contributors to the world’s CO2 emission, namely the United States of America and Australia,

† Annex I countries: Australia, Austria, Belarus, Belgium, Bulgaria, Canada, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Latvia, Liechtenstein, Lithuania, Luxembourg, Monaco, Netherlands, New Zealand, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom, United States of America. ‡ Annex II countries: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Luxembourg, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, United States of America.

10 have not ratified the Protocol. Their main reasons for not ratifying the Protocol are China’s exemption from GHG emission reduction and claims that such strict limitations on GHG emissions would pose a threat to their national economies. Additionally, the United States consider the split between Annex I and developing countries as unfair, because both developing countries and developed countries should reduce their emissions [12]. Now recent estimates indicate that China meanwhile has overtaken the United States as the world’s largest CO2 emitter by 8% [13], it is not likely that either the United States or Australia will ratify the Protocol shortly. Alternatively, in January 2006, the United States and Australia have, together with China, India, Japan, and South Korea, unified in a non- treaty agreement for cooperation and development of new technologies to mitigate GHG emissions, known as the Asia-Pacific Partnership on Clean Development and Climate (APPCDC or AP6). In the framework of this agreement, China and India are given an opportunity to build on market incentives to cut their GHG emissions, and since the partner nations account for 45% of the global gross domestic product (GDP), 50% of the GHG emissions, and 48% of global energy use [14], the agreement has the potential to drastically cut global GHG emission. However, the AP6 partners have agreed not to put any strict limitations on their emissions for now, so it is unclear when or whether emission reductions will take place and, if so, to what extent. It is for this reason that the use and effectiveness of the AP6 is broadly questioned, also in the AP6 countries themselves [15], and is even referred to as a pact between the biggest users of fossil fuels to maintain their leading position in the world economy [16]. On a subnational scale, a large number of emission reduction projects is being carried out at the moment. Most notable projects of this type are the initiatives in Australia and the United States. The Australian state of New South Wales (NSW) launched the NSW Greenhouse Gas Abatement Scheme (GGAS) as of January 1, 2003, to allow for emission trading among householders in NSW [17]. In the United States, as of April 20, 2007, ten northeastern states are united in the Regional Greenhouse Gas Initiative (RGGI) to reduce GHG emissions [18] and a similar emission limitation programme exists in the state of California since the Global Warming Solutions Act passed the Legislature on August 31, 2006 [19]. Further, as of August 10, 2007, 648 mayors from all states, representing more than 72 million Americans, have signed the United States Mayors Climate Protection Agreement, which urges the United States Congress to enact policy to the Kyoto Protocol’s targets, while trying to meet these targets in their own communities [20]. Finally, environmentalists are trying to create more awareness on the matter of global warming among a worldwide audience e.g. by promoting Al Gore’s documentary film “An Inconvenient Truth” [21] and the recently organised series of worldwide concerts “Live Earth” [22]. There is much more to be said on global warming politics, since it is an increasingly hot item in the media at the time of writing. Because of the vast amount of information available on the matter, the complex political interests at stake and the uncertainties concerned in the projections for global warming, sea level rise etc., it is very difficult to formulate a comprehensive, yet neutral section on the matter. As a final

11 example of the complexity, it is worth mentioning the response of the

Chinese government to the news that China is now the world’s largest CO2 emitter (see [13]): groundless and in need of better understanding of China and its economy. In support of this opinion, Greenpeace, China has stated that Western countries have shifted their carbon footprint from their own soil to Chinese for economic reasons, leading to a dangerous climate disaster in the future, and that a shared responsibility is necessary now [23]. It should thus be clear that the political part of this section cannot be considered as fully comprehensive, but merely as an optimistic attempt towards an overview on the subject of global warming politics.

2.2 The global energy market

2.2.1 Energy resources and consumption Since the start of the industrial revolution around 1750, mankind has relied upon the use of fossil fuels such as oil, natural gas and coal to provide in its energy need. Since recent decades, however, there is a growing awareness and concern about the GHG emissions resulting from the use of these fuels, which are predominantly used for electricity generation and transport. The consequences of this style of energy consumption and the possible scenarios, with which future generations will be faced, have been illustrated in the previous section. In this section, an attempt is made to quantify the use of the several energy resources. Widely used sources for this type of information are the data from the Energy Information Administration (EIA) [24], which is a part of the United States Department of Energy, British Petroleum (BP) [25], and the Renewable Energy Policy Network for the 21st Century (REN21) [26]. One should be aware of the significant uncertainty (at least 10%) in the numbers shown in this section. Estimates on the availability of resources are adjusted frequently (especially the oil and gas reserves), because of newly-gained scientific insights, increased measurement accuracy, and economic stakes, and can therefore only be valued on their orders of magnitude, rather than on their exact amounts. The uncertainty in the energy consumption data is moreover due to the fact that the energy consumption is not equally carefully monitored in each country. According to the EIA, the currently remaining fossil fuels amount for an estimated 400 ZJ (1 ZJ = 1021 Joule), the theoretically available energy from nuclear fuels such as uranium exceed 2.5 YJ (1 YJ = 1024 Joule) and the Sun provides the Earth with an energy flux exceeding 3.8 YJ/a. The sheer magnitude of the last numbers, and the last one in particular, becomes clear when comparing them to the average global energy consumption in 2004: 473 EJ/a (1 EJ/a = 1018 Joule per year). This is about 8,000 times less than the annual solar energy flux. When comparing these numbers to the ones in a report by the World Energy Council (WEC) [27], there is a difference: the energy from both fossil and nuclear fuels together add up to 325 ZJ, which is about 19% less than the EIA projection. As mentioned earlier, these numbers are highly uncertain, which makes it difficult to ignore the possibility of political interests being at stake here. The WEC annual solar radiation is estimated as 2.9 YJ/a, which is lower than the EIA’s estimate, but still of the same order. The

12 estimate on the global energy consumption (425 EJ/a) is also comparable to the EIA data. Still, in both cases it seems that the fossil and nuclear energy resources are not very close to depletion, as they can theoretically supply mankind’s energy demand for more than six centuries. What is imperative to realise, however, is that such a scenario is highly undesirable considering the consequences for the global climate system and the world economy, as will be explained in the following subsection. A graphical representation of both energy resources and power consumption is shown in figure 2.4.

(a)

(b)

Figure 2.4: Estimation of (a) energy resources and (b) power consumption in 2004 subdivided in the different types of energy sources. Graph (a) is taken from [27] and originally from [28]; graph (b) is created from [25] and [26].

What should be clear from figure 2.4 is that only a small amount of the consumed power is currently generated from renewable resources (about 4%, excluding biomass and nuclear as renewables), while the energy that could be obtained from renewable resources – and solar energy in particular – is much larger than the annual consumption. Finally, it should be mentioned, however trivial it may seem, that the fossil fuels are depleting and as a whole not even represent a fraction of the energy available from the renewable resources in a single year.

2.2.2 The need for renewable energy The global power consumption and the corresponding atmospheric GHG concentration have risen steadily since the start of the industrial revolution in the 19th century (see figure 2.1), which is strongly related to the temperature and sea level rise and the decrease in global snow cover, as is depicted in figure 2.2. As can be concluded from the previous sections, political action is already taken now to prevent further increases in GHG concentration and surface air temperature. It is becoming increasingly certain that the use of fossil fuels will no longer be economically viable in the near future, because of its potential to perturb ecosystems and economies. In addition to this, fossil fuel reserves are shrinking, although it cannot be said with any certainty when fossil fuels, such as oil and coal, will be depleted completely. In figure 2.4, it seems that oil in particular is close to depletion, but opinions on when this will happen exactly vary so widely that it is hard to state anything definite on the year of depletion except for the fact that it will occur in the near future. Some report 2006 – 2007 as the years of peak oil price [29], while others state this will not happen prior to 2025 [30]. Without trying to estimate the year in which the oil will be depleted, or at least no longer economically viable to extract, it is clear that oil cannot be a major energy resource in the future. The same statement does not directly hold for coal, because coal is much more abundant than oil and therefore the year of peak coal is much further away than the year of peak oil. At 2005 production levels, proven coal reserves were estimated to last for about 155 years [31]. Coal-fired power plants however, are one of the largest sources of CO2 emission, which is the primary contributor to global warming. Additionally, coal is a very impure material, containing substantial amounts of heavy metals and smaller quantities of radioactive isotopes. In spite of the low radioactive content in coal, the use of burning coal for electricity generation is so widely spread that the world’s coal-fired power plants account for more radioactive waste than the nuclear power plants [32]. Finally, the carbon content of coal is higher than the carbon content of oil, making coal the most serious threat to the stability of the Earth’s climate. Considering these negative aspects, coal cannot be considered as a future energy resource, even though it is currently cheap and very abundant in nature. The currently rising problem with coal is that it is extensively used in rapidly growing economies, just because of its low price and wide availability, especially in China, where, as of 2007, about two coal-fired power plants are built every week [33].

The third widely used fossil fuel for electricity generation is natural gas.

Because the combustion of natural gas emits almost 30% less CO2 than oil and almost 45% less CO2 than coal, natural gas is considered a relatively clean fossil fuel. Further, the combustion of natural gas releases very small amounts of sulphur dioxide (SO2) and nitrogen oxides and virtually no ash or particulate matter, which are released when coal or oil are burnt. Nevertheless, natural gas reserves are limited, although the gas reserve is projected to last longer than the oil reserve (estimates range from 60 to 200 years [34]). Even though the main constituent of natural gas is CH4, which is about 21 times more effective as a GHG than CO2, it has a relatively short atmospheric lifetime (about 12 years), making it an interesting candidate for mitigating GHG emissions from the use of oil and coal. Moreover, it has been calculated that the reduction in emissions from increased natural gas use strongly outweighs the detrimental effects of increased CH4 emissions [35]. Taking these advantages into consideration, it is impossible to deny the beneficial use of natural gas for electricity generation on a short-term scale. For the long term it still holds, just as for the other fossil fuels, that using natural gas will eventually no longer be economically viable and CO2 emissions will still rise to unacceptably high levels. As an alternative to fossil fuels and their adverse effects on the environment, fissile fuels (uranium, plutonium and thorium) are considered by some countries (e.g. United States, United Kingdom, and

France) for mitigating CO2 emissions. It is true that a nuclear power plant does not directly emit CO2, making fissile fuels a cleaner source of energy, but the enrichment of uranium is in general not a clean process [36]. The electricity required for uranium enrichment is normally generated by burning coal, since no country (except for France) has enough nuclear power plants to enrich uranium solely with electricity from fissile fuels. The Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency and the International Atomic Energy Agency (IAEA) have projected that the uranium resources will last for at least 85 years and possibly 2,500 years more when fast reactor technology, in which more fissile material is produced than consumed, is further developed and implemented on a large scale [37]. Without even criticising the accuracy of these numbers, some critical remarks can be made about the possible use of nuclear energy on a global scale. The biggest problem with fissile fuels is the radioactive waste, which has to be stored safely for several thousands of years. Apart from the cost necessary for implementing vast numbers of storage vessels, there is the ever-present danger of accidents in a nuclear power plant (especially if large numbers of reactors would be constructed worldwide), the possibility of creating nuclear weapons from the waste and the chance of a terrorist attack on a nuclear power plant or waste storage. The combination of the risks involved in the use of fissile fuels on a large scale and the limited amount available make it very difficult to acknowledge the possibility of a nuclear- powered global electricity supply in the future. Since GHG emissions and their negative impact are not restricted by the borders of the emitting country, action on both a national and an international scale is required. To meet the global energy demand in a more sustainable way, i.e. by not using fossil or fissile fuels, several plans have been proposed. There are several reports available containing

15 projections of future energy use based on different assumptions for electricity generation, economic growth and population growth. Reports from the EIA [24], the International Energy Agency (IEA) [38], the German Advisory Council on Global Change (WBGU) [39], and the most recent report by Greenpeace International and the European Renewable Energy Council (EREC) [40] are all extensive and well-known reports reviewing one or more future energy use scenarios. The prime aspects of the projections outlined in these reports, however, vary substantially. The EIA primarily projects a business-as-usual (BAU) scenario (energy use trends from the last decades are extrapolated into the next three decades without any significant changes; see figure 2.5 – figure 2.7), while the others stress the importance of a sustainable global energy supply and present alternatives. The increase of global CO2 emissions resulting from this BAU scenario are not shown in this report because they are approximately proportional to the increase in energy use, since no substantial increase in renewable energy resources is projected in this scenario.

Figure 2.5: World marketed energy consumption as projected by the EIA’s BAU scenario. 1 Quadrillion Btu (= British thermal unit) corresponds to 1.055 EJ. Graph is taken from [24].

Figure 2.6: World marketed energy use by fuel type as projected by the EIA’s BAU scenario. Liquids in this graph are referring to oil. Graph is taken from [24].

Figure 2.7: World electricity generation by fuel type. The BAU scenario identifies coal as the future’s most important resource for satisfying the global energy demand. Graph is taken from [24].

The IEA outlines a BAU reference scenario, similar to the reference scenario from the EIA, and an alternative scenario, in which an expansion of nuclear energy and energy from biofuels is primarily presented as a sustainable solution to mitigate global CO2 emissions. Additionally, the IEA report proposes a more efficient use of energy resources as a means to diminish the CO2 emissions. The expected savings from this approach are depicted in figure 2.8.

Figure 2.8: Global savings in CO2 emissions in the IEA’s alternative scenario compared to the reference scenario. Graph is taken from [38].

The WBGU report is more in line with the SRES and the main conclusions from the TAR – the AR4 was not written yet when the WBGU report was published – and outlines a roadmap to a sustainable global energy supply, including an extensive list of policy measures necessary for reaching this. The resulting shift in the energy mix can be seen in figure 2.9. A notable difference with the other reports is the continuously growing importance that is ascribed to solar power. This role of solar power in the world’s energy mix of the future is acknowledged and supported by the photovoltaic (PV) industry, as will be discussed later on in section 2.5.

Figure 2.9: Transforming the global energy mix: the exemplary path until 2050 and 2100 according to the WBGU. Graph is taken from [27], but is originally from [39].

Where the WBGU does not go into detailed calculations to prove the economical feasibility of the suggested major turnover in the way the world’s energy is generated, the Greenpeace / EREC report does present extensive projections expressed in numbers of future energy use per resource, which is required for reaching the “sustainable world”. In the latter report, a more efficient use of the generated electricity, increased investments in renewable energy resources (solar, hydro, biomass), and a phase-out of non-renewable energy resources are emphasised. The shift in the world’s energy mix from the IEA reference scenario towards a more sustainable scenario, as calculated in this report, is shown in figure 2.10. A notable difference with the WBGU report is the more distributed increase in the use of all renewable energy resources, as opposed to the dominance of solar energy in the WBGU report. Still, by 2050, 70% of the electricity produced worldwide is projected to come from renewable energy sources, which is more than projected by the WBGU.

Figure 2.10: Development of global electricity generation under the IEA reference scenario (above) and the Greenpeace / EREC alternative scenario (below). Graph is taken from [40].

Fully understanding the origin of all the numbers presented in the graphs in this subsection is only possible after having read the reports from which the graphs have been taken. Explaining this would demand a lot of space in this report and perseverance from the reader, so instead the reader is encouraged to personally review [24], [27], [38], [39], and [40]. What should be clear is that continuing to generate electricity from fossil and fissile fuels, as has been done during recent decades, is no longer an option for future generations. This makes appropriate (political) action required now to fundamentally transform today’s energy systems onto a more sustainable basis to avoid the otherwise very likely adverse effects of global warming on tomorrow’s society and economy.

2.2.3 The importance of photovoltaic technology As mentioned in the previous subsection, an important role is ascribed to PV technology in the global energy mix of the future. In the framework of mitigating global warming and protecting the world’s environment from the consequences of increasing atmospheric GHG concentrations, this is easily explained by the National Renewable Energy Laboratory’s (NREL) estimate of the GHG emissions reduction that is achieved by using PV instead of non-renewable energy resources: for every kilowatt (kW) of PV- produced electricity, the emission of 830 pounds (lb) of nitrogen oxides,

1,500 lbs of SO2, and 217,000 lbs of CO2 is avoided (1 lb = 453.59237 g) [41]. This large emission reduction is possible because only relatively small amounts of waste materials and GHG emissions come from the production of PV systems and their transport. Apart from this, PV systems burn no fuel and do not produce air pollution, hazardous waste, or noise while operating. Other advantages of PV technology include [42]:

• The modular nature of the technology enables a distributed electricity generation, increasing reliability of the power supply, decreasing distribution and transmission costs, and mitigating the impact of natural or anthropogenic disasters on the energy production. The modularity further enables PV systems to be designed such that the energy need for a specific application is accurately met. • A more global use of PV technology will moderate the dependence of the current global energy need on international energy politics and volatile fossil fuel-based markets. • With a life expectancy of 30 years and an energy pay back time (the time required to recover the energy that went into making a PV system) of approximately 1 – 4 years, 87% – 97% of the energy produced by a PV system will be free of pollution, GHG emissions, and depletion of resources [43]. • Even though the costs of PV-generated electricity cannot compete with retail prices yet, this is expected to happen shortly (e.g. 2015 for Southern Europe, followed by the rest of Europe 5 to 10 years later) due to continuously falling production costs of solar cells [44]. • PV systems are highly reliable and do not contain any moving parts, making them very low in maintenance, except for visual checks and servicing of the battery and the converter. • In remote areas, where grid connections are unavailable and in general very costly to install, PV systems are ideal to generate the required electric power. This advantage is especially important when it is considered that some 2.4 billion people, mainly in rural parts of Asia and Africa, lack access to modern forms of electricity and depend largely or entirely on biomass for electricity generation [39]. • The PV market offers important social benefits in terms of job creation: when the recent market growth rates are maintained, some 2 million people can be employed in the global PV business by 2020 [45]. • When PV systems are integrated into buildings, savings can be made on otherwise needed conventional materials required for the construction of e.g. windows.

2.3 Overview of the photovoltaic industry

2.3.1 Historical technological overview Now it has been explained that renewable energy, and PV technology in particular, can and has to play a prominent role in the future energy supply of the world, an overview of the photovoltaic industry will be given

20 in this section, starting with an historical overview of the different technologies. In 1839, a first basis was laid for the development of solar cell technology when the photovoltaic effect was discovered by Becquerel [46]. While experimenting with a solid electrode in an electrolyte solution, he observed a voltage and a current whenever light was incident on the electrode. The effect itself was however not very well understood, but the recognition of photoconductivity between two platinum (Pt) electrodes separated by a slab of vitreous selenium (Se) [47] still resulted in the first solar cell made from Se coated with a very thin layer of gold (Au) in 1883 [48]. A first physical-mathematical explanation of the observations was made possible by Einstein’s famous publication on the photoelectric effect in 1905 [49], which was experimentally confirmed by Millikan in 1915 [50]. In the following years, several materials were investigated for the application in solar cells, such as copper oxide (Cu2O), cadmium sulphide (CdS), lead sulphide (Pb2S), and thallium sulphide (Tl2S). The existence of the PV effect in silicon (Si) was discovered by Ohl in 1941 due to a p-n interface naturally occurring during the crystallisation process of Si [51], but at that point still no solar cell with an energy conversion efficiency of more than 1% had been reported. After an exploration of the role of positive (p-type) and negative (n- type) dopants in controlling semiconductor properties, the breakthrough came in 1954 when researchers from Bell Labs succeeded in fabricating a silicon solar cell with an efficiency of 6% by using phosphorus (P) to create a shallow p-n interface in a controlled manner [52]. This discovery triggered the beginning of the commercial exploitation of PV technology in 1955. Production numbers stayed at low levels until the 1970s; the high price of PV technology in those days did not enable the possibility for exploiting PV on a large scale, but the use of solar cells in space applications was an immediate success. The majority of the solar cells were then made of monocrystalline silicon (mono c-Si), later followed by multicrystalline silicon (multi c-Si) [53]. These so-called first-generation solar cells used for terrestrial applications consist of two oppositely doped semiconductor layers (p-type and n-type) of c-Si stacked on top of each other, forming a single p-n junction. Since then, a vast research effort has been spent on further understanding the semiconductor materials and improving the properties of c-Si. For this reason, c-Si is today’s most extensively studied solar cell material, resulting in a still significant market share of c-Si solar cells (see figure 2.11). There are however several disadvantages of using c-Si in the production of solar cells: the wafer- based process required for obtaining c-Si is expensive and the amounts of necessary material are relatively large. To investigate the possibility of increasing the solar cell conversion efficiency, research interest moved towards multiple-junction cells (stacks of materials with different band gaps absorb a wider range of the solar spectrum, see section 3.3.3) and different materials, such as gallium arsenide (GaAs), amorphous silicon (a-Si), and more recently cadmium telluride (CdTe), copper indium diselenide (CuInSe2 or CIS), and copper indium gallium diselenide (CuInGaSe2 or CIGS). The resulting second- generation silicon solar cells are now known as thin-film (TF) silicon solar cells because of the reduced amount of required material. Typically, the efficiencies of thin-film solar cells are lower when compared to their first- generation silicon (wafer-based) counterparts, but since manufacturing

21 j

(a)

(b)

Figure 2.11: Changes of cell technology shares in the PV market (a) since 1980 and (b) since 1999. In these graphs, Cz (Czochralski, the process used for producing monocrystalline Si) is equivalent to mono c-Si, Px (polycrystalline Si) is equivalent to multi c-Si, and thin film refers to CdTe, a-Si, and CIS together. Other thin-film Si-based technologies have been included in the a-Si figure, since their market share is very small. Even though the market share of thin-film PV is currently rising again (mostly due to CdTe), the market is still largely dominated by wafer- based first-generation solar cells. Graph (a) is taken from [56]; graph (b) is taken from [55].

costs per unit area are lower, a lower cost per Watt can be achieved. Dye- sensitised solar cells (DSSC) and polymer solar cells also fall into this category, but it should be noted that their conversion efficencies are low and they are still in the research phase. In an attempt to lower the cost of solar cells, while maintaining a high conversion efficiency, quantum dot solar cells and advanced concepts such as up/down converters are currently being investigated. These so-called third-generation solar cells are, however, still in the research phase and commercial production has not started yet, so in this section no further attention will be paid to these types of solar cells. To clarify the differences between the now discussed

Technology c-Si Heterojunction TF Si CIS CdTe DSSC Efficiency [%] with Intrinsic (stable) Thin layer (HIT) Record cell 24.7 (mono) 21.3 9.3 (single) 18.9 17.0 11 (not 20.3 (multi) 12.4 (tandem) stable) 13.4 (triple) Record 22.7 (mono) ? 10.4 13.4 10.7 4.7 module 15.3 (multi) Commercial 12 – 17 16 – 17 5 – 9 9 – 11 6 – 7 not module available Future cost limited limited large large large large? reduction

Table 2.1: Current status of the different solar cell technologies in terms of conversion efficiency. Expensive technologies that serve a niche market, such as GaAs, have been omitted from this table, since they form a negligible fraction of the total PV market. Thin-film technologies show lower conversion efficiencies than c-Si, but this does not phase out second-generation technology in favour of c-Si, because of the lower cost per area. Table data are taken from [57].

different types of solar cells and the progress that has been made for each technology, a summary of the conversion efficiencies of the commercially available modules is given in table 2.1 for each technology, as well as the record efficiencies of solar cells and modules that have been achieved in a lab environment. In spite of the advantage that second-generation solar cells have over c-Si solar cells in terms of production cost, the PV market is currently still largely dominated by first-generation solar cells. The reason for this is that PV companies are taking a financial risk when entering the thin-film PV market, since the technology is less mature than the first-generation PV technology (e.g. lower efficiencies, lower stability over time, and less understanding of the used materials) and economical success does not appear to be guaranteed, translating into a decreasing market share of thin-film PV technologies up until 2004 [54]. Recently, however, production numbers of especially CdTe cells and modules have risen significantly, increasing the market share of thin-film PV [55]. This indicates that the market is starting to respond to the low-cost potential of thin-film solar cells. A graphical representation of the recent changes in market shares of the different PV technologies is given in figure 2.11.

2.3.2 The recent growth of the photovoltaic industry Since 2001, an extraordinary average annual growth of the PV industry of 41% has been reported, resulting in an average growth rate of 35% per year since 1976. Annual growth rates have never been that high before (disregarding the 1976 – 1981 period, when the market was still dominated by specific off-grid applications and overall sales volumes were very small) and no other energy-generating technology is showing growth numbers of that magnitude [56]. In absolute numbers, this comes down to a production output of 2.54 gigawatt (GW) in 2006 [55] compared to 0.2 megawatt (MW) in 1976 [56], which means the PV industry has increased production by a factor of 12,700 in 30 years. Since 2005, the PV industry is using even more silicon than the microelectronics industry,

Figure 2.12: Production numbers of the top 10 cell producers and the market shares per region in 2006 and 2005. China’s market share has clearly increased very heavily in one year, threatening the leading position of Japan. Graph is taken from [55].

thus creating a shortage of available silicon [58]. It should be clear that this shortage is only due to the silicon producers’ current incapability to keep up with the growth of the PV industry and definitely not by a lack of silicon as a whole, since Si is the second most abundant element in the Earth’s crust (after oxygen). Because of the feedstock shortage, which is projected to last at least until 2008 – 2010 [59], the recent high growth rates seem even more impressive. The recent market share increase of thin-film PV technology is at least partially due to the feedstock shortage and the currently high prices of silicon, making it impossible for many c-Si PV companies to produce at full capacity [55]. Over the last years, the world’s PV market has been dominated by companies from Japan (Sharp, Kyocera, Sanyo, Mitsubishi Electric) and Germany (Q-Cells, Schott Solar) because of significant political interest in PV technology in those countries, but the recent growth of Mainland Chinese and Taiwanese companies (Suntech, Motech) has become so large, that China is likely to become the world leader in cell production in 2 – 3 years. Before the dominance of these countries, BP Solar and Shell Solar were among the largest producers, but since they did not expand their business as fast as their competitors and, in the case of Shell, even sold their German production facilities to SolarWorld in 2006, their market shares have dropped heavily [55]. To illustrate these recent changes in the PV market, the production numbers of the top 10 cell producers and the market shares per region from the last two years are given in figure 2.12. The given overview of the photovoltaic market is only attempting to be comprehensive, but there is more to be told about the evolution of solar cells and the rise (and fall) of the different PV technologies. To avoid

24 diverging further is this report, the reader is referred to excellent overviews on this matter, such as [53] and [60]. Because the technology of the solar cells investigated in the remainder of this report is a-Si, some more attention will be paid to the historical technological developments in this field in section 3.1, while an overview of the historical market developments in TF a-Si solar cells is presented in the following section.

2.4 Developments in thin-film amorphous silicon solar cells As discussed in section 2.3.1, a-Si technology was first introduced in the 1970s as a part of the first thin-film or second-generation solar cells. The first commercial introduction to the market was in 1980 by Sanyo and Fuji Electric for consumer electronics applications, such as calculators and watches. Expectations of the new technology were high, since it required 100 – 1000 times less silicon compared to the first-generation c-Si solar cells to absorb the same amount of usable solar energy. Additionally, the plasma-enhanced chemical vapour deposition (PECVD) technique, used for depositing the active layer of the solar cell, enabled the production of large area modules at a lower temperature. This meant less energy was required for the fabrication and low-cost materials, like glass, metal and later also polymer foil, could be used as a substrate. These advantages made a-Si technology into an interesting option for the production of low-cost thin-film solar cells, especially for off-grid power generation in remote places. Throughout the 1980s however, a-Si technology started to suffer from an image problem, caused by an insufficient moisture protection of the commercially available modules, resulting in corrosion of the module contacts, and a significant degradation of the solar cells’ active material upon illumination, otherwise known as the Staebler-Wronski effect (SWE; see section 3.4). Stabilised efficiencies of these first modules reached up to 5%. During the next decade, several companies started producing modules based on double- and triple-junction a-Si technology (BP Solar, Sanyo, Fuji Electric, United Solar), but the market share stayed small compared to the traditional wafer-based c-Si solar cells. The application of a-Si technology shifted from off-grid to building-integrated power generation. After the introduction of a new type of double-junction (or tandem) solar cell in 1994, consisting of an amorphous silicon top solar cell and a microcrystalline silicon (μc-Si) bottom solar cell, a renewed interest in a-Si technology arose. Before 1994, the bottom cell in a tandem solar cell was made using an alloy of Si and germanium (Ge). In the new micromorph tandem solar cell however, the use of the expensive Ge had become obsolete, making the micromorph concept interesting for the fabrication of low-cost thin-film solar cells. The potential of micromorph tandem and triple-junction solar cells was soon proven by accomplished stabilised efficiencies of 11% to 12%, and it did not last long before the micromorph solar cell was commercialised by Japan’s Kaneka Corporation [61]. Several technological issues were, however, not solved yet (a-Si’s lower conversion efficiency compared to c-Si, the SWE, slow deposition rates of the absorber layers, etc.), making the economic viability of mass- production doubtful. For this reason, the PV industry was most probably reluctant to invest in the micromorph or other thin-film technologies,

25 causing its market share to shrink because of an increasing market share of the first-generation technologies (see figure 2.11). As discussed in section 2.3.1, a revival of thin-film technologies has recently started and its market share is now expanding again, triggered particularly by the current silicon feedstock shortage [59]. In 2006, the a-Si production numbers went up to 118 MW from 85.9 MW in 2005, although its market share stayed constant at 4.7% (see figure 2.11b). The market leader position in the a-Si market is currently split between United Solar and Kaneka, each producing 28 MW in 2006. Other companies in the PV market account for the remainder of the total production capacity, including Mitsubishi Heavy Industries (13 MW), Shenzhen Topray (10 MW), Sharp (8.2 MW), Bangkok Solar (6.8 MW), and Sanyo (5 MW) [55]. Compared to the total production capacity of about 30 MW in 2000 [61], the 37% increase of last year is rather large, which is due to the fact that the production of the machinery that is required to fabricate solar cells for the a-Si market has only recently been commercialised by Applied Materials and Oerlikon. Considering the currently high Si price and the projected increase of the PV industry as a whole, the market share of thin- film PV is expected to grow further in the coming years. According to predictions from the companies forming the a-Si PV market, production numbers are said to increase to 150 MW in 2007. It is important to remark that this number is in fact a low estimate, because it still excludes an additionally projected capacity increase of 145 MW in 2007 [55]. Considering the silicon shortage, it is not certain up to which extent this capacity can be used and therefore the projected capacity increase has been neglected in the production projections.

2.5 Future developments in thin-film solar cells

2.5.1 Renewable energy policy developments From the start of a-Si technology into the PV market on, a-Si has been identified as a promising candidate for low-cost thin-film solar cells. For reasons discussed in section 2.4, a-Si technology did not meet the initially high expectations, but this is about to change. Firstly, there are the threats of global warming, outlined by the IPCC, which are taken more and more seriously by governments and companies over the world, as discussed in section 2.1. In this framework, there is a growing lobby for renewable energy, backed up by several scientifically supported reports, some of which were discussed briefly in section 2.2. All of these reports ascribe an important role to PV technology in supplying the world’s future energy demand, albeit not to the same extent in each report. In general, these reports project a modest, yet significant, energy market share of PV around 2030 and a dominant market share in the subsequent decades. In order to realise the projected market share of PV in the energy mix of the future some difficulties have to be overtaken. As already outlined in section 2.2, the global energy consumption is virtually certain to increase throughout the 21st century because of globally increasing wealth. To ensure that PV will make a significant contribution to the world’s electricity generation in the future, the recent public and political interest in renewable energy should not only be maintained, but

26 expanded. An important example of a major political factor in this matter is the upcoming negotiation period between the countries that have ratified the Kyoto Protocol which is expiring in 2012. While the European Union (EU) countries have already posed stricter limitations on their own GHG emissions than initially agreed upon in the Kyoto Protocol (20% versus 8% emission reduction) to cut down their emissions at a higher rate [62], other industrialised countries (e.g. Canada which intends to join the AP6 instead of complying to the Kyoto Protocol requirements [63]) are failing to meet the required GHG emission reduction in 2012. Until the Kyoto Protocol expires, the political debate will continue between the nations that have ratified the Protocol. In this framework, delegates of these nations met in Germany in May 2007 to discuss the post-2012 agreements and how to solve current tough political problems, such as how to involve the United States, which did not ratify the Kyoto Protocol, and how to deal with the prior exemption of important polluters (mainly China, India, and Brazil) from the Kyoto Protocol commitments [64]. If these problems are not properly addressed, the international debate would lose its credibility and influence, resulting in a more fragmented approach to overcome the negative consequences of global warming. In such a scenario, only industrial countries would be capable of supplying in their own need, whereas developing countries would suffer even more from global warming than they do today because of insufficient financial resources. It is for this reason that the developing countries and the renewable energy lobby call out for investments from the industrialised countries, aiding the developing countries in building a modern infrastructure, and better controlling the GHG emissions, without impeding their economic growth.

2.5.2 Technological developments Apart from the political issues that have to be tackled, several technological problems of PV technology have to be solved before it can be applied on a worldwide scale to substantially contribute to the world’s power generation mix. Without immediately going into the details of the different problems faced by the different PV technologies, it can be said that the price of PV has to decrease to make it more interesting in economical terms. Again, politics should play a role here by funding the purchase of PV systems and arranging attractive feed-in tariffs for PV- generated power, but the industry and research community should also focus on decreasing the production costs. It seems obvious to state now that the efficiency of solar cells should increase, but it is even more important to ensure an overall low price, i.e. decreasing the sales prices by increasing the production scale, minimising the energy required for the production of solar cells to reduce the pay back time of the solar cells, and minimising the environmental load during production. Additionally, module prices are largely determined not by the cost of the actual solar cells, but merely by the costs of module packaging and the used solar cell substrates [61]. In this respect, thin-film technologies are easily preferred over the traditional wafer-based c-Si technology when the proper measures are taken, which explains the current research interest in this technology and the projected increase in market share.

As mentioned before in section 2.3.1, several thin-film technologies are commercially available, but the economic advantage that these technologies have over c-Si cannot be easily attributed to each of these technologies when they would be expanded to worldwide production now. Ideally, the future PV technology should be inexpensive, non-toxic, and readily available. Unfortunately, none of the presently available thin-film technologies has all of these properties. For instance, even though CdTe is a very efficient light-absorbing semiconductor (see table 2.1) and its market share in the thin-film market has recently increased by a relatively large amount (see figure 2.11b), true mass-production would be faced with safety problems. Cadmium (Cd) is a highly toxic material and storage in large quantities for mass-production is potentially harmful, as well as the disposal of CdTe modules at the end of their lifetime. Further, it is doubtful whether developed countries would not pose legislative restrictions on large-scale storage of a toxic substance such as Cd, thus preventing distributed mass-production. Finally, tellurium (Te) is a rare, expensive element (168 €/kg) and is currently extracted as a by-product in copper (Cu) and nickel (Ni) production. This makes it difficult to predict future Te prices, but prices are not bound to go down, since it is unlikely that today’s by-product would become tomorrow’s main product in production only because of an increasing demand for solar modules. Therefore, CdTe cannot be the main technology implementing the projected growth of the PV market in the long run, although it offers some possibilities for use on a short term because of its relatively low price and efficient energy conversion capabilities [65]. The currently most efficient thin-film solar cells and modules are based on CIS (or CIGS), making this technology automatically a potentially interesting candidate for large-scale production and energy supply. Unlike CdTe, there is no danger of toxicity from any of the components in CIS technology. This has tempted more companies to enter the CIS market rather than the CdTe market, although the total quantity of produced CIS modules is much smaller than the output of the CdTe modules manufacturers (see figure 2.11b). The reason why the market share of CIS technology is not increasing in spite of its advantages is easily explained: the extremely high costs of the required indium (In). Like Te, In is a rare element obtained as a by-product during aluminium (Al) and zinc (Zn) production. As mentioned earlier for the case of Te, this production method is the cause of a highly uncertain future In price, since In buyers do not reveal their actual demand to avoid a price increase, causing the In sellers not to increase production to a high level because they do not know what the demand is. As a consequence of this tension in the In market, the In price has increased by about 1300% between 2002 and 2006 to 775 €/kg, seriously threatening the economic viability of CIS module production. Taking into account the uncertainty in the In price that is inherent to the market, it has become increasingly difficult to rely upon CIS technology for the future’s energy supply [65]. Now the pros and cons of CdTe and CIS have been discussed, there is just one established group of thin-film PV technologies to be discussed: the Si-based technologies. The enormous Si resource available is the most prominent advantage of these technologies, including a-Si, μc-Si, nanocrystalline Si (nc-Si), polycrystalline Si (poly-Si), and combinations of these in multi-junction configurations. As mentioned several times now,

28 this technology is suffering from a current shortage of Si and a consequently high Si price (155 €/kg), but this will be solved on a short term when the planned Si production capacity increase will be completed and the Si price will subsequently decrease to 15 – 20 €/kg [54], making TF Si potentially the cheapest of all thin-film technologies. There are, however, several difficulties related to thin-film Si, which have created a sceptic attitude towards the potential of large-scale production of e.g. a-Si modules. Firstly, the efficiency of a-Si modules has to be increased, because it is significantly lower than the efficiencies of CdTe and CIS modules (see table 2.1). There are, however, strong indications that this can be improved shortly by an increase in the output current of a-Si modules, which will be realised by improved light trapping techniques and reduced absorption losses. Secondly, the Staebler-Wronski effect causes a typical decrease of 15% – 30% in the initial performance of an a-Si module, which does not occur in other first- or second-generation modules. This disadvantage of a-Si-based solar cells and a method to diminish the SWE will be further discussed in the following chapters, as it is one of the main topics of this report. Further, the throughput of the machines used for depositing the active layer of the solar cell is relatively low, making it difficult to amortise the investment in this machinery in a reasonable amount of time. Increasing the deposition rate of the absorber layer seems the obvious solution, but until now this has proven to be difficult, since absorber layers deposited at increased deposition rates suffer more severely from the SWE [61]. Since the remaining chapters of this report will focus on a-Si technology, no further discussion will be devoted here to a comparison of the different TF Si technologies; the interested reader is, however, referred to [67]. Considering the advantages and disadvantages of the thin-film PV technologies presented earlier in this subsection, there is a strong indication that TF Si will significantly contribute to the projected increase of the PV market. However, as long as the technological problems of TF Si are not solved, the market share of other TF technologies, such as CdTe and CIS, is likely to increase. In general, it can be said that TF technologies have to become more mature before they can push the first- generation technologies out of the market, but since a global research effort is currently spent to achieve this, a domination of TF technologies in the PV market of the future is very likely. More information about the future PV market developments and price evolutions of the different technologies can be found in [61], [62], and [68]. As a means to implement the projected increase in grid-connected PV systems, the use of very large scale PV (VLS-PV) systems has been proposed. A number of detailed feasibility studies of placing VLS-PV systems in several different deserts in the world is described in [69]. Finally, it is interesting to mention the increasing amount of research spent on new second- and third-generation solar cells, including organic, dye-sensitised, and quantum dot solar cells. Theoretically, the cost of these solar cells can be lower than the cost of Si-based second-generation solar cells, because of cheaper materials (e.g. polymers versus Si) and cheaper production equipment (e.g. spin coating versus PECVD). All third- generation technologies are however still in the research phase as they are not yet commercially produced, and because of limited understanding of the used materials, predictions on the role of these technologies in the

29 future are highly speculative and are therefore not further considered in this report.

3 The properties of amorphous silicon In this chapter, an overview is given of the properties of amorphous silicon, which is required for fully understanding the content of the following chapters. First, in section 3.1, a historical overview is given of the technological developments in the field of amorphous silicon solar cell technology. This is followed, in section 3.2, by a description of the different types of silicon that are used in solar cells. In section 3.3, a discussion is presented of the material parameters that characterise hydrogenated amorphous silicon, followed in section 3.4 by a discussion of the photo-induced degradation, otherwise known as the Staebler-Wronski effect. Finally, hydrogenated amorphous silicon solar cells and its properties are discussed in section 3.5.

3.1 Historical overview The first experiments with amorphous silicon were performed in 1965 when the first a-Si layers were deposited by means of radio frequency glow discharge deposition, or plasma-enhanced chemical vapour deposition (PECVD), from silane (SiH4) gas [70]. The semiconductor properties, and hence the possible use of a-Si in solar cells, were however not recognised before 1975, when it was demonstrated that a-Si could be changed from intrinsic (i-type) material into p-type or n-type material by adding diborane (B2H6) or phosphine (PH3) gas to the SiH4 during the deposition [71]. Around the same time, it was discovered that a-Si deposited by glow discharge was in fact an alloy of Si and hydrogen (H), resulting in a new name for the deposited material: hydrogenated amorphous silicon (a-Si:H) [72]. Using the right gas mixtures, p-type, i- type, and n-type a-Si:H could now be deposited, resulting in the first a- Si:H solar cell with an energy conversion efficiency of 2.4% in 1976 [73]. This efficiency greatly contrasted with the very low efficiencies of non- hydrogenated amorphous silicon solar cells that had an active layer deposited from sputtering instead of PECVD. For this reason, it became clear that hydrogen played an important role in achieving device-quality material. Since then, the research interest in a-Si:H increased quickly and the first a-Si:H solar cells and modules were shortly thereafter introduced to the market, as was described earlier in section 2.4. In spite of the great cost-wise advantages a-Si:H offered over c-Si (high absorption coefficient in the visible part of the solar spectrum and possible large-area and low- temperature deposition using PECVD), several issues prevented a-Si:H solar cells from becoming a dominant player in the PV market, as was initially expected. An important technological drawback of the early a-Si:H modules, however, was their short lifetime due to e.g. encapsulation problems, which resulted in a corrosion of the metal contacts. Another disadvantage of a-Si:H was (and is) the photo-induced degradation of the material (SWE), which will be discussed in more detail in section 3.4. As mentioned in section 2.4, there was a renewed interest in a-Si:H after the introduction of the micromorph tandem solar cell in 1994 [74]. This type of solar cell, consisting of an a-Si:H top absorber layer and a hydrogenated microcrystalline silicon (μc-Si:H) bottom absorber layer,

31 offered a low-cost alternative to hydrogenated amorphous silicon germanium (a-SiGe:H) that was used before as a bottom absorber layer. Further, μc-Si:H has a lower band gap than a-SiGe:H (1.1 eV versus 1.45 eV), so a larger range of the solar spectrum can be absorbed when μc-Si:H is used instead of a-SiGe:H. During the following years, a-Si:H in the micromorph configuration was commercialised and, recently, the market share of solar cells based on a-Si:H has stopped to decrease and promising production numbers are expected for 2007 (see figure 2.11b and section 2.4). The advances in the field of μc-Si:H are not within the scope of this report and will thus not be discussed further. More information on this matter can be found in [61], as well as a more extensive discussion on other technologies that comprise a-Si:H.

3.2 The different types of silicon As discussed in the above and earlier sections, different types of Si are used in solar cells, which absorb different ranges of the solar spectrum. The types – or phases, as they are more commonly referred to – of Si that have been mentioned so far are a-Si:H, μc-Si:H, and poly-Si. Recently, the use of the terms protocrystalline silicon (pc-Si:H) and nanocrystalline silicon (nc-Si:H) has appeared. By definition, a-Si:H and pc-Si:H do not contain any crystals. The other types of Si derive their name from their feature size: hydrogenated polycrystalline silicon (poly-Si:H) contains the largest crystals, followed by μc-Si:H [75], while nc-Si:H has the smallest crystals. It is not clear when precisely a material should be called μc-Si:H or nc-Si:H, since there is no consensus on an exact crystal size that borders the two. Because the crystal size in μc-Si:H is in fact in the order of nanometres, nc-Si:H is considered by some as a more appropriate name for μc-Si:H. This means that μc-Si:H and nc-Si:H refer to the same material. To avoid confusion caused by poorly defined terminology, the use of the term nc-Si:H will be avoided from now on. A more extensive

Figure 3.1: Schematic representation of the atomic structure of (a) c-Si, (b) μc-Si:H, and (c) a-Si:H. In c-Si, all Si atoms are covalently bonded to four other Si atoms. Graph is taken from [57].

32 summary of the discussed phases of Si:H and their properties is given in both [61] and [75]. To illustrate the differences in structural order between c-Si, μc-Si:H, and a-Si:H, schematic representations of the atomic structure of these types of Si are depicted in figure 3.1. In c-Si, all Si atoms are covalently bonded to four other Si atoms. The angles between all bonds are identical and all bonds have the same length. This high regularity is not present in μc-Si:H, where the long- range order is only to be found in some parts of the material. Outside of these so-called grains, just a short-range order remains, also known as a continuous random network, and the bond lengths and angles differ from atom to atom. Where μc-Si:H still contains grains, a-Si:H contains only a continuous random network and the short-range order is not in excess of a few atomic distances. Further, in a-Si:H, the angles between the bonds are not identical for all bonds and not all bonds have the same length. Therefore, some bonds in the continuous random network are known as weak or strained bonds, as they are easily broken when sufficient energy is available, for instance in the form of heat. In the continuous random network, some Si atoms are only bonded to three instead of four Si atoms, resulting in a so-called dangling bond. Such a dangling bond can be passivated by a hydrogen (H) atom; when this is not the case, it is called an unpassivated dangling bond or a defect. Hydrogen passivation, which is a natural consequence of the use of silane for depositing a-Si:H, plays an important role in trying to reduce the number of dangling bonds in a-Si:H to a device-quality level. Another type of defect in the continuous random network appears when a Si atom is covalently bonded to five other Si atoms, also known as a floating bond [61]. Both types of defects are illustrated in figure 3.1b and figure 3.1c as a red line (dangling bond) and a red circle (floating bond). Si:H layers deposited by PECVD (or any other glow discharge deposition method) from H2-diluted SiH4 contain at least to a small extent an amorphous part, since the first few deposited nanometres (nm) of material consist of a-Si:H. The thickness of this so-called incubation layer is, however, very small in device-quality μc-Si:H and therefore the amorphous fraction is not reflected in the name of this material. The crystalline fraction of the deposited material strongly depends on the

Figure 3.2: The hydrogen dilution of silane during PECVD deposition of Si:H films induces a phase change from pc-Si:H to mixed (a+ μc)-Si:H and finally to μc-Si:H when the film is grown to a sufficient thickness. Graph is taken from [76].

Figure 3.3: Bright field electron micrographs of Si:H layers of an equal thickness (~1 μm) deposited on glass with different hydrogen dilution ratios R. As illustrated in figure 3.2, the crystalline fraction of the film increases for an increasing value of R while the thickness is kept constant. Graph is taken from [77].

substrate on which it is grown, the thickness of the deposited layer, the hydrogen-to-silane dilution ratio R = [H2]/[SiH4], and other deposition conditions (pressure, rf-power, substrate temperature, etc.), as will later be demonstrated in chapter 5. The regime according to which Si:H films grow from H2-diluted SiH4 is known as the protocrystalline growth regime and only when the deposited material is fully amorphous (meaning the layer did not grow to a sufficient thickness to form crystals), it may be referred to as pc-Si:H [76]; otherwise the material is defined as mixed- phase Si:H ((a+ μc)-Si:H) or μc-Si:H. To illustrate how the transition from the amorphous to the microcrystalline phase is dependent on the thickness of the grown layer and the H2 dilution of the SiH4 used during the PECVD deposition, a schematic drawing of this process is given in figure 3.2, and a series of bright field electron micrographs of Si:H films deposited at different R values is depicted in figure 3.3.

3.3 Material parameters of hydrogenated amorphous silicon

3.3.1 Density of states distribution To understand the charge transport in a semiconductor like a-Si:H, it is essential to have some knowledge of the distribution of the states in the material. This distribution is widely known as the density of states (DOS) distribution and is necessary for an analysis of both native and photo-

34 induced defects in a-Si:H, as will become clear in section 3.4. For (ideal) intrinsic c-Si, there are no allowed energy states between the valence band edge EV and the conduction band edge EC. Therefore, it is possible to define the difference between these two energy levels unambiguously as the band gap Eg, which reflects the minimum photon energy that is required to excite an electron from the valence band to the conduction band, i.e. the minimum photon energy required for inducing a photocurrent. For a-Si:H, however, the same reasoning does not hold. As has been discussed in section 3.2, there is no long-range order in the atomic structure of a-Si:H. Therefore, a conduction and valence band edge cannot be defined in the same way as is done for c-Si. Instead of the sharply defined extended or non-localised states in c-Si where the charge carriers can move freely, the energy states of the conduction and valence band in a-Si:H spread into the band gap; these localised states are known as tail states. These tail states are due to weak Si-Si bonds, which are due to the structural disorder in a-Si:H (see section 3.2). Further, in a-Si:H, there is a continuous distribution of localised states between the tail states of the valence and the conduction band due to defects, such as dangling bonds [61]. A schematic comparison of the densities of states of both c-Si and a-Si:H are presented in figure 3.4.

Figure 3.4: Schematic comparison of the densities of electronic states distributions of (a) c-Si and (b) a-Si:H. In c-Si, a clear band gap of 1.1 eV can be identified. In a-Si:H, it is only possible to define a mobility band gap, which is approximately 1.8 eV. Graph is taken from [57].

Even though there is no well-defined band gap between the valence and conduction band in a-Si:H, it is possible to define a mobility band gap

Emob. This name is used because the mobility of the charge carriers in the localised states (the tail and defect states) is much smaller than it is in the non-localised states (the extended states). Similarly, it is still possible to use EV and EC, but in a-Si:H they refer to respectively the valence band mobility edge and the conduction band mobility edge [57]. The DOS distribution of a-Si:H as illustrated in figure 3.4b is generally agreed upon. However, there is no consensus on the exact DOS distribution of the defect states between the tail states. In general, the

Figure 3.5: Standard schematic representation of the density of states distribution in a-Si:H with two Gaussian distributions modelling the differently charged defect states. The energy difference denoted as U is known as the correlation energy, which is assumed to be constant. Graph is taken from [61].

defect states are represented by two Gaussian distributions centred about different energies, which are separated by the correlation energy U, as can be seen in figure 3.5. There are three possible charge states for a dangling bond: positive (D+), neutral (D0), and negative (D-). Therefore, in the band diagram, a dangling bond is represented by two transition energy levels which characterise the charge occupation of the dangling bond. The Gaussian distributions about these two transition energy levels (D+/0 and D0/- from figure 3.5) are then to be interpreted as energy distributions of the states that correspond to dangling bond charge transitions between the positively charged state and the neutral state and between the neutral state and the negatively charged state. Although the Gaussian distributions are in line with the idea that the structural disorder in the continuous random network gives rise to a distribution of states instead of states located at particular energy levels, they do not explain the origin of defect states. A widely used model of the DOS distribution in a-Si:H that does include a physical explanation of the origin of defect states is the so-called Defect-Pool Model (DPM) [78],[79]. In the DPM, dangling bonds are created from broken weak Si-Si bonds, broken Si-H bonds, and doubly hydrogenated Si-Si bonds. Due to the structural disorder in the continuous random network, it is assumed that the energy of a defect is not restricted to one particular value. Further, the DPM suggests that a defect can be formed in each of the three different charge states that are defined in the model. The total defect density is then calculated as the sum of three energy distributions, corresponding to positive, neutral, and negative defects. Note that the three density of defect distributions cannot be described by a simple

Gaussian, as they are also determined by the occupancies of the three charge states, which are functions with an exponential energy dependence that strongly affect the density of defect distributions at low and high energies. Without going into the further mathematical details of the statistical mechanics used in the model, it should be mentioned that the DPM predicts an increase in the total number of dangling bonds in intrinsic a-Si:H where the Fermi level EF shifts towards EV or EC. This means that there is a rapid increase in the defect density at e.g. the interface of a p-type and an i-type layer of a-Si:H; a similar argument can be made for an interface of n-type and i-type a-Si:H. Since a-Si:H solar cells are in general based on a p-i-n structure, relatively high recombination losses are thus to be expected at the p-i and n-i interfaces. More information about the DPM and several preceding models can be found in [75] or [61]. The above-mentioned discrepancy in the modelling of defect states between the general model and the DPM is caused by the lack of a direct method to measure or determine the DOS distribution in a-Si:H. Therefore, information about the DOS is obtained in an indirect way, e.g. by means of measurements of optical and/or electrical properties of a- Si:H films. A number of these opto-electrical measurement methods, which are used to calculate the absorption coefficient spectrum, will be described in chapter 4.

3.3.2 Absorption coefficient spectrum To evaluate the quality of an a-Si:H film (or any other photo-sensitive material) and estimate the defect density of the material in an indirect way, the absorption coefficient spectrum is an important figure of merit. It is used, for instance, to calculate the DOS distribution, which has been discussed in the previous subsection. As has been mentioned in section 2.4, about 100 – 1000 times less Si is required when a-Si:H instead of c- Si is used as the active layer in a solar cell. This is clear from the absorption coefficient spectrum: for a-Si:H, the optical absorption coefficient α is almost 100 times higher in the visible part of the solar spectrum than it is for c-Si due to a lack of long-range order in a-Si:H. As discussed in section 3.2, the order in the atomic structure of μc-Si:H is lower than it is in c-Si, but not as low as in a-Si:H, resulting in an α spectrum of which the values lie in between the α values of c-Si and a- Si:H for the visible part of the spectrum (400 nm – 700 nm). The different α spectra and the corresponding penetration depth spectra (d = 1/α) of these three phases of Si are depicted in figure 3.6. The absorption coefficient spectrum of a-Si:H from figure 3.6 can be subdivided into three regions. Firstly, there is the high-absorption region where direct electronic excitations from the valence to the conduction band are involved. This region is determined by the band gap of the material, which has been discussed earlier in section 3.3.1, and corresponds to the energy values larger than the band gap. The energy corresponding to α = 104 cm-1 can give a first rough estimate to the phase of the material and can be easily obtained from this energy region of the α curve. In the remainder of this report, this energy level will be referred to as E04 [75]. As is clear from figure 3.6, E04 increases with

Figure 3.6: Typical absorption coefficient spectra and corresponding penetration depth spectra of c-Si, μc-Si:H, and a-Si:H device-quality layers on glass. The red line is the Urbach line, which is used to calculate the Urbach energy EU. The red shaded area refers to the absorption that is due to defect states in the middle of the band gap. This graph is adapted from [80].

increasing crystallinity. The second region that can be recognised is characterised by an exponentially decreasing α towards lower energies. Regarding figure 3.5, it can be said that the absorption for these energies corresponds to transitions involving the tail states in a-Si:H, because the DOS shows exponentially decaying valence and conduction band tail states. To obtain information about the distribution of the tail states, it is therefore customary to estimate the α in this mid-energy region by fitting it to an exponentially decreasing function, whose exponent is known as the

Urbach energy EU:

α = α0 exp(E/EU), (3.1)

where α0 is a constant, E the photon energy, and EU the exponential slope of the energy dependence [81]. The parameter EU is widely used to indicate the material quality, because it tells something about the disorder of the material, which gives rise to weak bonds, as has been discussed earlier in section 3.3.1. Values of EU below 40 meV for μc-Si:H, and below 50 meV for a-Si:H, are considered to indicate device-quality material. For illustrative purposes, the required fit to the α spectrum in the mid-energy range and the resulting Urbach line are depicted in figure 3.6. Finally, there is the low-energy region where the absorption is due to electron transitions from the defect states in the middle of the band gap to the extended states. In other words, the sub-band gap absorption

38 represents the absorption due to defects in the intrinsic layer of a solar cell, which is a major factor limiting the performance of a thin-film solar cell [61]. Later in chapter 5 and 6, this sub-band gap absorption will be used to estimate the defect density Nd. One way of calculating Nd from the α spectrum of a-Si:H is to integrate the area under the α curve over the defect states [82], which is indicated as the red shaded area in figure 3.6, after which the integrated absorption is multiplied by a proportionality factor of 7.9×1015 cm-3. Note that although this proportionality factor has been determined by combining several physical constants, there is no 16 -3 broad consensus on its exact value. Values of Nd below 10 cm are considered to correspond to device-quality a-Si:H [75].

Another method commonly used to estimate Nd in a-Si:H from the α spectrum is to use α1.2 eV, the absorption coefficient at 1.2 eV. In a-Si:H, this absorption coefficient value is characteristic for the material quality, since for such a low energy the value of α is directly related to defects that act as recombination centres in the middle of the band gap. To obtain -1 a value for Nd now, it is required to multiply α1.2 eV (expressed in cm ) by a calibration factor of 2.4 – 5×1016 cm-3, which has been empirically determined by comparing Electron Spin Resonance (ESR), Constant Photocurrent Method (CPM), and Photothermal Deflection Spectroscopy (PDS) measurement results [83]. Each of these measurement methods do, however, have their drawbacks, which will be further discussed in section 3.4.

3.3.3 Optical band gap As mentioned in the two preceding subsections, c-Si, μc-Si:H, and a-Si:H have different (mobility) band gaps. As a consequence of this, these three materials have different absorption coefficient spectra, as can be seen in figure 3.6, and different parts of the solar spectrum are absorbed, which is illustrated in figure 3.7. Apart from the band gaps that have been introduced hitherto, the so- called optical band gap Eopt can be defined for a-Si:H, which can be obtained from the material’s optical properties confined in the α spectrum. Whereas Emob is roughly defined by the change in mobility of the charge carriers between the non-localised and the localised states (see section 3.3.1), Eopt defines the energy difference between the extended states of the valence and the conduction band by using the α spectrum. The calculation of Eopt is performed by extrapolating the function (α(E) n(E) E) 1/(1+p+q) versus E to α(E) = 0 (for α(E) ≥ 103 cm-1):

1/(1+p+q) (α(E) n(E) E) = B (E – Eopt), (3.2) where α(E) is the energy-dependent absorption coefficient, n(E) is the energy-dependent refractive index, p and q are constants that describe the shape of the DOS in the extended states of the conduction band and valence band, respectively, and B is a pre-factor. For crystalline materials, it is commonly assumed that the DOS distributions near EC and EV have a square root energy dependence, meaning that p = q = 1/2. Assuming these values for p and q, equation 3.2 describes the so-called Tauc plot and the corresponding optical band gap is known as the Tauc gap ET [85].

Figure 3.7: The different band gaps of c-Si, μc-Si:H, and a-Si:H cause different regions of the solar spectrum to be absorbed by each material. This graph is adapted from [84].

If the DOS distributions near EC and EV have a linear energy dependence, this means that p = q = 1; in this case the optical gap is referred to as the cubic gap or Klazes gap EK [86]. For device-quality intrinsic a-Si:H, ET < 1.8 eV and EK < 1.6 eV; in general EK is about 0.1 – 0.2 eV smaller than ET [61].

3.4 Photo-induced degradation: Staebler-Wronski effect An important drawback of using a-Si:H as a material for solar cells is the degradation of the material upon illumination, otherwise known as the Staebler-Wronski effect. As discussed in section 2.4, the SWE is one of the factors that prevented a-Si:H from becoming a dominant material used in the PV industry. The effect was first recognised in 1977 by Staebler and Wronski, who observed a significant decrease in dark conductivity and photoconductivity of glow discharge-deposited a-Si:H after prolonged illumination. These changes were found to be metastable, i.e. reversible by annealing the material at temperatures above 150 °C. Initially, no clear physical explanation of the observations could be given, but the changes in conductivity – or the changes in lifetime of the charge carriers – were attributed to a reversible increase in the density of localised gap states acting as recombination centres for photo-excited charge carriers, causing the dark Fermi level EF to shift towards mid-gap [87]. In the following years, many attempts have been made to characterise and understand the physics of the SWE better, triggered by the generally high research interest in a-Si:H during the 1970s and 1980s. Summarising, it can be

40 said that there was a qualitative consensus on the above-stated explanation proposed by Staebler and Wronski as of 1985. The quantitative conclusions from the different experiments, however, did not agree at all. It was not clear what the absolute density of metastable states was, neither was there agreement on their position in the mobility gap, nor whether one or more types of defects would appear upon illumination. Further, it was not clear whether the SWE in a-Si:H was predominantly determined by the surface or by the bulk properties of the material. It was however, broadly assumed that the SWE could be microscopically explained by the breaking of Si–Si bonds upon illumination, resulting in metastable dangling bonds (DBs), as proposed by the Stutzmann-Jackson-Tsai (SJT) model [88]. The SJT model states that the majority of the electrons and holes created by band-gap illumination recombine through DBs that act as effective recombination centres in the middle of the band gap and were already present directly after the formation of the continuous random network (i.e. before the a-Si:H sample is illuminated), while a smaller part recombines directly (band-to-band recombination). Because the latter process is very exothermic, the resulting phonons can break weak Si–Si bonds in the continuous random network. Therefore, it is suggested that these Si–Si weak bonds should have a nearest neighboring H atom, and the Si–H bond is exchanged with the Si-DB created by breaking the weak Si–Si bond just after the weak bond is broken, as is shown in figure 3.8. As a result, the two created Si-DBs are stabilised. The secondly formed DB can also move along the continuous random network by bond switching, but a H atom has to stay nearby. This step is not further illustrated in figure 3.8. Stabilisation in time occurs when no sufficient Si-H bonds remain to allow the formation of Si-DB bonds, meaning that any broken Si-Si bond is restored again, so no additional DBs are formed.

Figure 3.8: Atomic configuration of a-Si:H (a) before illumination and (b) after illumination. Graph is adapted from [91].

Later, it appeared from ESR measurements that any H atom should either be more than 0.4 nm apart from a photo-induced DB or closer than 0.05 nm. Because a DB should always be accompanied by a H atom in the continuous random network according to the SJT model, the ESR measurement results are not consistent with the model. This problem gave rise to a new model in 1997 [89], known as the hydrogen collision model, which could better explain the SWE in both a quantitative and a qualitative way. In 1999, a more elaborate discussion of the model was

41 presented by the same author [90]. In the H-collision model, mobile H atoms are created by photo-excited carriers that break Si-H bonds, resulting in DBs. Just as in the SJT model, the majority of these DBs is annihilated immediately, because most of the mobile H atoms rebind with pre-existing DBs. With a much smaller probability, two mobile H atoms can collide with each other and form a so-called metastable complex of two Si-H bonds, as depicted in figure 3.9. Note that the two DBs that are now stabilised, are formed differently from the formation of DBs in the SJT model, where DBs are formed after breaking Si-Si bonds.

Figure 3.9: Two examples of possible atomic configurations of a metastable complex of two Si-H bonds in the continuous random network. Note that the two DBs that are stabilised by the metastable complex are not depicted in the figures. Graph is taken from [91].

Using the H-collision model, it is possible to avoid the above-described problem of the SJT model, since two separated DBs can be created with no nearby H atoms, which is consistent with the ESR measurement results. Unfortunately, the H-collision model is not without problems either. In this model, it is assumed that mobile H atoms are the cause of DB creation, as opposed to the DB creation solely due to photo-generated charge carriers. Hitherto, it has not been possible to unambiguously verify whether mobile H atoms are indeed predominantly responsible for the creation of DBs. Without further discussing the details of the above-discussed and dozens of other models that try to capture the properties of the SWE, it can be said that a full understanding of the problem and a proper solution to it still lack. What is currently clear is that photo-created DBs are not mainly caused by impurities, such as oxygen (O), nitrogen (N), and carbon (C). Further, it appears that the presence of H in the continuous random network plays an important role in the formation of DBs upon illumination, but it is not clear whether this is a direct or an indirect role [91]. Finally, it should be noted that apart from the mentioned obscurities surrounding the SWE, another problem lies in the measurement methods used for obtaining Nd. The commonly used ESR method can only identify defects associated to a neutral DB (paramagnetic defects), because such a defect results in an unpaired spin signal. Charged defects can thus not be detected by ESR which can result in underestimating Nd if EF is not close to mid-gap. Another way of obtaining Nd is by estimating it from the

42 absorption coefficient spectrum, as has been described in section 3.3.2. To obtain the absorption coefficient spectrum, several methods are available, which will be discussed in detail in chapter 4. For now, it is sufficient to state that also these methods have their drawbacks. For instance, CPM is, unlike ESR, capable of detecting both neutral and negatively charged DBs, but DBs near to the surface, where the defect density is relatively large, are not detected [92]. These measurement limitations make it difficult to accurately determine Nd, which at its turn impedes the development of models that describe the physics of the SWE.

3.5 Hydrogenated amorphous silicon solar cells

3.5.1 Solar cell structures As has been mentioned before in section 3.3.1, a-Si:H solar cells are in general based on a p-i-n or n-i-p structure. These configurations are different from the typical p-n structure that is used for c-Si solar cells. To be able to explain this difference, it is required to have some understanding of the mechanisms that are responsible for the photocurrent in both c-Si and a-Si:H solar cells. The heart of a solar cell is the absorber layer, in which photons create electron-hole pairs. In c-Si solar cells, the absorber layer typically consists of a moderately doped p-type c-Si layer. In order to generate a photocurrent, the photo-created charge carriers have to be separated and collected at opposite sides of the absorber layer, where the front and back contact of the solar cell are located. Therefore, on each side of the absorber layer, a layer is located that only allows one type of charge carrier to pass through to the contact, which usually consists of Al. For electrons, a heavily doped n-type layer is used and for holes a heavily doped p-layer, since only electrons can easily flow through heavily doped n-type material, whereas holes are more mobile in a heavily doped p-type material. The heavily doped layers thus provide a low-ohmic connection to the contacts of the solar cell, while acting as a barrier for one of the two charge carrier types [57]. A schematic overview of the general structure of a c-Si solar cell can be seen in figure 3.10a. Close to the interfaces of the absorber layer and the two heavily doped layers in a c-Si solar cell, depletion regions are formed as a consequence of the formation of a p-n junction, which means that internal electric fields are created at these interfaces. These electric fields facilitate the separation of electron-hole pairs and sweep electrons and holes towards the heavily doped layers. However, the majority of the photo- created electron-hole pairs is not generated in one of the internal electric fields of the p-n junctions in the solar cell. For this reason, it is said that diffusion of the charge carriers is the dominant transport mechanism in c-Si solar cells, because the majority of the charge carriers first has to diffuse towards the p-n junctions before the electric fields can sweep them towards the heavily doped layers. When a photo-created electron-hole pair is not separated in a sufficiently short amount of time, it will recombine and the charge carriers will not reach the depletion regions, i.e. not contribute to the photocurrent.

Figure 3.10: General structure of (a) a c-Si solar cell and (b) an a-Si:H solar cell. The yellow arrows indicate the direction of the incident light. Graph is taken from [57].

The transport of the minority charge carriers in a-Si:H works differently from the mechanism present in c-Si. In a-Si:H, the ambipolar diffusion length Lamb of the charge carriers is much shorter than it is in c-Si, where Lamb is typically greater than the thickness of the absorber layer. For a- Si:H, this means that the vast majority of the charge carriers would recombine before reaching the contacts. Therefore, a structure relying predominantly on the diffusion of photo-generated charge carriers through the quasi-neutral regions of the p-n junctions (those parts of the p-n junctions where there is no internal electric field) cannot be used for a-Si:H solar cells. To still separate the photo-created electron-hole pairs, an electric field has to be created in the whole absorber layer. This is done by inserting an intrinsic layer of a-Si:H between a p-type and an n-type layer, which are connected to the contacts of the solar cells. The back contact usually consists of Al and/or silver (Ag), while the front contact is usually made of a transparent conductive oxide (TCO), such as tin oxide

(SnO2) or zinc oxide (ZnO). A general example of the resulting p-i-n structure is illustrated in figure 3.10b. Under influence of the electric field, electrons move towards the n-layer and holes towards the p-layer. Because the transport mechanism is now predominantly determined by the electric field in the i-layer, the drift of the charge carriers is considered to be the dominant transport mechanism in a-Si:H solar cells [57]. Since all solar cells investigated in the remainder of this report have a p-i-n structure, figure 3.10 does not display the general structure of an n-i-p a-Si:H solar cell, neither will the aspects of this type of solar cell be discussed in further detail. It should be clear now that the electric field strength and profile in the i-layer of an a-Si:H solar cell are important factors in the performance

44 of the solar cell, since they dictate the collection of the photo-generated charge carriers. The quality of the i-layer is another influential parameter that has to be considered, since the defect density and distribution in the bulk of the i-layer strongly determine the electric field profile. Due to the significant amount of localised states in the band gap of a-Si:H, carriers can be trapped by these states and thus not contribute to the photocurrent and, additionally, create a charge build-up which disrupts the electric field profile. According to the DPM (see section 3.3.1), the defect density in the i-layer is high in those parts of the i-layer that are close to the interfaces with the doped layers, which creates a relatively large electric field in these parts of the i-layer, while the electric field is relatively low in the bulk of the i-layer [61]. To investigate the possibility of minimising these detrimental effects of defect states in the centre of the band gap on the performance of an a-Si:H solar cell, a structured optimisation of several deposition parameters is described in chapter 5. Apart from optimising the i-layer of an a-Si:H solar cell, several other parts of the solar cell should be considered before a highly efficient solar cell can be achieved. For instance, the absorption in the p-layer should be minimised since the vast majority of the photo-generated carriers in the p-layer do not contribute to the photocurrent. For this reason, the p-layer should be thin (~10 nm) and have a band gap that is greater than the band gap of the i-layer. A commonly used method to achieve this high band gap is by adding CH4 to the gas mixture during the deposition of the p-layer, which results in the growth of a so-called hydrogenated amorphous silicon carbide (a-SiC:H) window layer. Further, to prevent back-diffusion of photo-generated electrons from the i-layer to the p-layer and optimise the electric field profile close to the p-i interface, a very thin (~5 nm) intrinsic or lightly-doped a-SiC:H buffer layer is usually deposited between the p- and the i-layer. This buffer layer also prevents boron (B) diffusion from the p-layer to the i-layer. Finally, a vast research effort is made to improve the light-trapping in the i-layer. This is done by using a textured instead of a smooth TCO layer and by increasing the reflection from the back contact by inserting a ZnO layer between the n-layer and the back contact, which both increase the average path length of the light in the i-layer [61]. Even though all these optimisations are very important, they are beyond the scope of this report and only the optimisation of the quality of the i-layer will be further considered.

3.5.2 Deposition techniques A widely used method for depositing device-quality a-Si:H layers that has been mentioned already several times in this report is radio-frequency (rf) plasma-enhanced chemical vapour deposition (PECVD). Because several deposition parameters will be varied to optimise the quality of the i-layer, as will be discussed in chapter 5, it is required to have a basic knowledge of how a PECVD system works. A schematic representation of an rf-PECVD system is depicted in figure 3.11. The deposition of a-Si:H is performed by dissociating a Si-bearing gas, usually SiH4, by means of a plasma which is created by an rf-power generator. Commonly, a plasma excitation frequency of 13.56 MHz is used to provide a source of energy which can dissociate the SiH4 molecules at

Figure 3.11: Schematic representation of an rf-PECVD deposition system. Graph is adapted from [57].

relatively low temperatures (typically 200 °C – 250 °C) into a mixture of different radicals and molecules, positive and negative ions, and electrons. Two radicals are supposed to play a particularly important role in the growth of a-Si:H layers: silyl (SiH3) and silylene (SiH2). These radicals precipitate on a substrate, which is attached to one of the two electrodes in between which the plasma is ignited. The growth process takes place in a stainless steel high vacuum chamber in order to prevent possible gas contamination during the growth of a-Si:H layers. In an attempt to suppress the Staebler-Wronski effect (see section 3.2), it has been shown that hydrogen dilution of the silane source gas during the rf-PECVD deposition is beneficial [93],[94]. This now commonly used method to diminish the SWE has proven to be capable of reducing the number of DBs in the grown a-Si:H layer and thus improve the quality of the i-layer. Therefore, it is important to be able to regulate the hydrogen-to-silane ratio R. The gas flows of both SiH4 and H2 can be controlled separately. Further, the gases B2H6 and PH3 are used for the deposition of respectively the p- and the n-layer, and can be regulated individually as well. All these gases can flow into the reaction chamber to deposit specific layers and can be pumped out of the reaction chamber when a different gas mixture is required for the deposition of the subsequent layer. In the particular PECVD system used for the deposition of the samples that will be investigated in chapter 5 and 6, the p-, i-, and n-layers are deposited in different reaction chambers to avoid cross contamination during the deposition. After the deposition, the reaction chamber is evacuated and outlet gases are consequently scrubbed or burnt in an exhaust system to prevent hazardous atmospheric contamination e.g. from the release of PH3, which is a very toxic gas.

The actual deposition process and the involved growth mechanism are not completely understood, but it has become clear that SiH3 radicals are the main contributor in the growth of device-quality a-Si:H layers. Further, the amount of SiH2 and other silane radicals in the plasma should be low, as the growth from these radicals results in low-quality layers [61]. To influence the quality of the deposited layer, several deposition parameters can be varied. In chapter 5, a structured optimisation procedure of the i- layer is presented and the influence of varying the plasma power, reaction chamber pressure, substrate temperature, and SiH4 flow (while keeping the hydrogen-to-silane dilution ratio R at a constant value) on the quality of the i-layer is investigated.

3.5.3 External parameters The performance of solar cells is usually characterised by their external parameters, which can be calculated from the current density versus voltage (J – V) characteristic. These electrical properties of the solar cell are usually obtained by illuminating the solar cell with a lamp that approaches the solar illumination with respect to the irradiance and the spectrum. Such an illumination system is referred to as a solar simulator and the lamp usually is a short-arc xenon lamp or a metal-halide lamp. The industrial standard for the irradiance is 1,000 W/m2 with an AM1.5 spectrum. These conditions are commonly referred to as the standard illumination conditions. Here, AM1.5 refers to an optical air mass of 1.5, which corresponds to a solar spectrum with a 48.2° angle between the position of the sun and the zenith. A typical J – V curve of an illuminated solar cell, which is obtained from the above-described JV measurement, is depicted in figure 3.12.

Figure 3.12: Typical J-V curve of an illuminated solar cell including several characteristic values. Graph is adapted from [57].

In figure 3.12, the intersections with the J and V axes are respectively known as the short-circuit current density Jsc and the open-circuit voltage Voc. Physically, Jsc is the photo-generated current density when the contacts of the solar cell are externally short-circuited and Voc is the voltage at which there is no external current flowing. In the latter case, the photo-generated current density is exactly compensated by the dark current density. From these two external parameters, the fill factor FF can be defined as:

JV FF = mpp mpp , (3.3) JVsc oc where Jmpp and Vmpp are the maximum power point current density and voltage, corresponding to the peak power point on the J – V curve. In physical terms, FF indicates the extent to which the solar cell approaches an ideal lossless diode. From the three external parameters of the solar cell, it is possible to calculate the most well-known figure of merit of the solar cell’s performance, which is sometimes referred to as the fourth external parameter: the conversion efficiency η. This conversion efficiency can be calculated by dividing the generated maximum power Pmpp by the power of the incident light Pin:

PJVJVFF η ==mpp mpp mpp =sc oc , (3.4) PPin in P in

2 where Pin is equal to 1,000 W/m [57]. In chapters 5 and 6, these parameters will be extensively used to verify the quality of several a-Si:H solar cell absorber layers deposited under different deposition conditions.

4 Measuring the absorption coefficient spectrum As has been discussed in sections 3.3.1 and 3.3.2, the absorption coefficient spectrum comprises important material properties of a photo- sensitive material, such as the DOS distribution. Further, the absorption coefficient spectrum can be used to obtain several material quality figures of merit, such as Nd, ET, and EK. The sub-band gap absorption is of special interest, because it is a measure for transitions from the localised states within the band gap to the extended states. Unfortunately, the sub-band gap absorption is a weak phenomenon, so indirect ways of measuring (i.e. via some secondary effect) are necessary to determine the absorption coefficient spectrum. As mentioned in section 3.3.2, several methods are available to determine the absorption coefficient spectrum. The advantages and disadvantages of a number of these methods will be the topic of this chapter. In sections 4.1 and 4.2, respectively, the conventional Reflection / Transmission (RT) method and Photothermal Deflection Spectroscopy (PDS) are discussed. Other established techniques for obtaining the sub- band gap absorption coefficient spectrum are the Constant Photocurrent Method (CPM) and Dual Beam Photoconductivity (DBP), which are treated respectively in sections 4.3 and 4.4. A more recently developed method, Fourier Transform Photocurrent Spectroscopy (FTPS), is the topic of discussion in section 4.5. Extra attention will be paid to the latter method, since it offers an interesting alternative to the other methods. An explanation is given of the suggested and implemented improvements of the particular system that is available in Delft University of Technology. The photocurrent spectra obtained from CPM, DBP, or FTPS can be used to calculate the sub-band gap absorption coefficient spectrum, as will be explained in section 4.6. Finally, in section 4.7, a qualitative comparison of the described methods is presented.

4.1 Reflection / Transmission The Reflection / Transmission (RT) method is the most conventional method used for obtaining the absorption coefficient spectrum of a material. While illuminating a (photo-sensitive) film deposited on a transparent substrate, the reflectance R and transmittance T of the whole structure are measured independently by two detectors. In the particular system used throughout this work, these detectors are calibrated Si and Ge photodiodes. The light is generated by a 100 W halogen lamp and illuminates the sample perpendicularly. To obtain the R and T data as a function of the photon energy (or wavelength), a Spex 1680B double grating monochromator is used that scans through the spectrum from 2.60 eV to 0.70 eV in steps of 0.02 eV. The most straight-forward way to calculate α from R and T is by using the following easy relation for the absorbance A:

ART= 1 −−, (4.1)

49 and the simplified Lambert-Beer equation:

Ad= 1exp()−−α , (4.2) where d is the thickness of the film. This results in the following expression for the absorption coefficient:

ln(1−+ART ) ln( ) α =− =− . (4.3) dd

This approach gives only a rough estimate of α, since it is assumed that there is no internal reflection from the back side of the film. Further, d has to be a known constant, which is in general not the case. Therefore, the use of a model that accounts for the reflectance and transmittance at each interface in the investigated sample is recommended. Such a model is implemented in the OPTA program developed at Delft University of Technology. This program calculates α by modelling the sample by the following layered structure: air–glass–film–air. The light is assumed to enter the structure on the glass side. For each layer, OPTA considers the energy-dependent complex refractive index:

ñnik= − , (4.4) where n is the real refractive index, i is the imaginary unit, and k is the extinction coefficient. For air and glass, n is considered to be energy- independent and assumed to be equal to 1 and 1.52 respectively, while k = 0 for both cases. This means that all absorption occurs in the film, since

khckλ α == , (4.5) 44ππqE where λ is the wavelength of the incident light. To express α as a function of the photon energy, the following wavelength-to-energy conversion factor is used:

hc 1240 E == , (4.6) qλλ where E is the photon energy expressed in eV, h is Planck’s constant in Joule-second (J·s), c is the velocity of light in vacuum in m/s, q is the charge of an electron in coulomb (C), and λ is the photon wavelength in nm. Because multiple reflections (interference fringes) appear at the film– glass interface and at the film–air interface, so-called effective Fresnel coefficients are used to calculate the net reflectance and transmittance of the film. These coefficients can be determined for each interface, resulting in a set of equations where only ñ and d of the film are unknown. Now OPTA is used to make a first estimate of d by using a standard set of n – k data which is characteristic for the particular film material. Thereafter, d is adjusted until a continuous and linear relation between n and E is obtained. Summarising, it can be said that the model estimates the k

50 values from the n values, after an appropriate value for d has been determined with OPTA. Further details of the model and the calculations using effective Fresnel coefficients of a stacked-layer structure are omitted here; the interested reader is referred to [75]. Finally, it should be mentioned that estimating k from n via a model can be avoided when the so-called Kramers-Kronig relations [95] are used. These mathematical properties explicitly connect the real and imaginary parts of ñ, making it no longer necessary to estimate k. Since RT only measures the reflectance and transmittance of a material, it is not sensitive enough to obtain accurate α values for energies below Eopt. For super-band gap absorption however, it is a widely used method since the measurement data are easily interpreted and result in an absolute α spectrum. To obtain the sub-band gap absorption, which contains useful information about the quality of the material, other methods than RT have to be used. A number of these opto-electrical methods will be discussed in the remaining sections of this chapter.

4.2 Photothermal Deflection Spectroscopy As described in the previous section, a measurement method other than RT is required to obtain the sub-band gap absorption. An example of such a method is Photothermal Deflection Spectroscopy (PDS), which is an opto-electrical method used for obtaining the absorption coefficient via a secondary effect. In PDS, this secondary effect is the phenomenon of changing a part of the absorbed photon energy into thermal energy (heating), which causes the index of refraction of the medium adjacent to the surface of the investigated film to change, whenever the film is struck by a beam of light. The medium adjacent to the surface of the film typically is a highly transparent liquid with a high thermal conductivity and a high temperature susceptibility of the index of refraction. During a measurement, a chopped monochromatic beam of light illuminates the sample. The thermally-induced change in refractive index of the liquid that appears upon illumination is in fact a temperature profile which decreases for increasing distance from the surface of the film. The gradient of the refractive index is a measure for the absorption of the film and can be measured by probing it with a laser just above the surface of the film. Because of the dissipated thermal energy close to the surface of the film, the laser beam is deflected. The distance over which the beam is deflected is a measure for the absorption of the sample and can be measured with a position-sensitive detector, such as a pair of coupled photodiodes. The most attractive feature of this measurement method is its high sensitivity, which makes it possible to measure low-absorbing materials as well. With the methods that will be discussed in the following sections it is not so obvious to measure low-absorbing films, since they rely on the conductive properties of the film. An important drawback of PDS is its sensitivity to surface states in the film, which causes an overestimation of

Nd when it is calculated from the α spectrum according to one of the methods described in section 3.3.2. Further, the extreme sensitivity of a PDS system to mechanical vibrations and ambient temperature fluctuations result in significantly longer measurement times when compared to any of the other methods described in the following sections.

A method to reduce the measurement time is described in [96], as well as an extensive overview of a particular PDS system and a comparison of PDS with the measurement methods that are treated in sections 4.3 – 4.5.

4.3 Constant Photocurrent Method As said in the beginning of this chapter, there is a number of opto- electrical methods which are used to determine the sub-band gap absorption. In the case of the Constant Photocurrent Method (CPM), this is done by means of a photoconductivity measurement [61]. This photoconductivity measurement is performed by illuminating the sample with chopped light that passes through a monochromator. The monochromator steps through a certain wavelength range to obtain the wavelength-dependent absorption of a film. A certain voltage is then applied to the electrodes that are deposited on top of the film. The voltage creates an electric field and separates the photo-generated electron-hole pairs. The current induced by this applied voltage is called the photocurrent and is used to calculate the photoconductivity as

I w σ = ph , (4.7) ph Uld where σph is the photoconductivity, Iph the photocurrent, U the applied voltage, w the distance between the measuring electrodes, l the length of the electrodes, and d the thickness of the photoactive layer. Further, it can be said that photoconduction is a process dependent on generation, transport, and recombination of excess photo-generated carriers. When it is assumed that the photocurrent is dominantly determined by electrons, transport and recombination are characterised by the mobility μ and lifetime τ of the electrons. The photoconductivity can then be expressed as

σ ph = qnqGμμτΔ= , (4.8) where q is the unit charge, Δn the concentration of the photo-generated electrons, and G the optical generation rate of the electrons. Remember now the Lambert-Beer absorption formula from equation 4.2, which correlates the absorbance A to the absorption coefficient α:

ARe=Φ0 (11 −) ( − −αd ) , (4.9) in which Φ0 is the incident photon flux density and R the reflectance from the air-film interface. Neglecting now the spectral dependence of the reflectance, the average generation rate can be approximated by

0 −αd A Φ−(11Re) ( − ) G ==ηη , (4.10) ggdd

52 where ηg is the number of electron-hole pairs generated by one absorbed photon, also known as the generation quantum efficiency. Substituting equation 4.10 in equation 4.8 results in:

Φ−0 (11Re) ( −−αd ) σμτη= q . (4.11) ph g d

In case of a CPM measurement, we are mainly interested in the steady- state photocurrent as a function of the photon energy in the sub-band gap region. In this region of photon energies, the absorption is weak, meaning that αd 1 . Using this fact, the following approximation can be made by expanding the exponential function to a power series:

ed−αd ≈−1.α (4.12)

Substituting this in equation 4.11 gives

0 σ ph=Φ−qRμτη g (1 ) α . (4.13)

Now it is possible to combine this expression for σph with equation 4.7, which results in the following expression for the photocurrent:

ld IUq=Φ−μτη0 ()1 R α , (4.14) phw g so it holds that

0 Iph∝Φμτη g α . (4.15)

The basic idea behind CPM is to keep the photocurrent constant, while changing the photon flux density, assuming that the term μτηg, also known as the quantum efficiency-mobility-lifetime product, is independent of the photon energy and remains constant during the measurement. Practically, this means that a control system is necessary, which measures both the power that is supplied to the light source in the CPM system and the induced photocurrent and adjusts the power of the light source in such a way, that the photocurrent is constant for all photon energies (or wavelengths) considered in the measurement. Physically, it means that the positions of the quasi-Fermi levels for both electrons and holes in the band gap, which determine the number of recombination centres, do not change during the measurement. In this way, the charge carrier lifetime is kept constant. When it is further assumed that the mobility of the carriers and the generation quantum efficiency are not spectrally dependent, the absorption coefficient is dependent only on the incident photon flux:

I ph CCPM α ()E ==00, (4.16) μτηgΦΦ()EE()

0 where CCPM is an energy-independent constant. In equation 4.16, Φ is not a constant, since the control system adjusts it in such a way that Iph is kept constant. Because the thus obtained photocurrent spectrum is relative, it has to be calibrated to the absolute absorption coefficient, which is typically obtained from an RT measurement. An important advantage of CPM with respect to PDS is that CPM does not measure the absorption of the substrate. Especially in defect regions, the substrate absorption can be dominant over the absorption of the film, if measured by PDS [97]. Due to a shorter carrier lifetime in the surface layer of the sample, CPM is generally less sensitive to absorption in this layer than PDS [98]. CPM only measures transitions which contribute to the photocurrent, which is dominated by electrons (mostly because the electron mobility is higher than the hole mobility), whereas PDS is sensitive to all electron and hole transitions. Since PDS is equally sensitive to both electron and hole transitions, it has been argued that PDS should give approximately twice the value that CPM gives for absorption due to just the neutral D0 defects [83]. This factor can be used to correct a PDS measurement, since PDS is sensitive to surface states and therefore PDS can overestimate the bulk density of states [61].

4.4 Dual Beam Photoconductivity A different method suitable for the evaluation of the sub-band gap absorption is Dual Beam Photoconductivity (DBP). DBP is to a large extent similar to CPM, but there is one important difference. In a DBP measurement, a strong direct current (DC) beam of light (bias) is used to keep the splitting of the quasi-Fermi levels constant during the measurement, in order to keep available states in the mid-gap region filled with photo-generated carriers [99] and to keep the carrier concentrations and lifetimes constant [100]. This means that the term μτηg from equation 4.15 is kept constant by the bias light. At the same time, a second chopped beam of monochromatic light (in the particular system used in this work, the chopping frequency is 13 Hz) illuminates the sample perpendicularly. The light beam is created by a 100 W halogen lamp combined with a Spex 1680B double grating monochromator. The generated photocurrent is fed to an EG&G 7260 lock-in amplifier, which locks in to the chopping frequency and selects the AC fraction of the photocurrent by means of filtering. This AC current depends on the monochromatic photon flux and the absorption coefficient of the sample [101]. The absorption coefficient is then calculated from the photocurrent and the photon flux density as

IE( ) α ()EC≈ ph , (4.17) DBP Φ0 ()E where CDBP is an energy-independent constant, Iph(E) is the photocurrent as a function of the photon energy and Φ0(E) is the photon flux density as a function of the photon energy. Note that this equation is very similar to equation 4.16, but now Φ0(E) is a constant. Contrary to CPM, in DBP the μτηg product is not kept constant by adjusting the intensity of the halogen lamp, but by the constant bias light. This means that DBP does not require

54 a control system that measures and adjusts the power of the light source. In the particular system used in this work, α(E) is obtained by letting the monochromator scan through the spectrum from 2.1 eV to 0.7 eV in steps of 0.02 eV. Just as in the case of CPM, this photocurrent spectrum is not absolute but relative, so it has to be calibrated to the absolute absorption coefficient spectrum measured by RT [61]. The procedure that will be used to perform the calibration in this thesis is further discussed in section 4.6. The advantage of DBP over CPM is the reduced measurement time. DBP measurements take less time, because it is not necessary to adjust the photon flux density during the measurement in such a way that the photocurrent is kept constant. Just as CPM, DBP is insensitive to surface states and substrate absorption, so just like a CPM measurement, a DBP measurement differs from a PDS measurement for the low energies (typically below 1.2 eV). The advantage of CPM with respect to DBP is that for low energies, a DBP measurement slightly overestimates the absorption coefficient. This is due to a decrease in the occupation of the states in the case of CPM with respect to the case of DBP, as CPM does not use DC bias light [102].

4.5 Fourier Transform Photocurrent Spectroscopy

4.5.1 Theory The last method discussed in this chapter that can be used to determine the sub-band gap absorption is Fourier Transform Photocurrent Spectroscopy (FTPS). As this method is frequently used to extract information from the sub-band gap absorption coefficient in the following chapters, it will be discussed in more detail than PDS, CPM, and DBP. An FTPS system uses the possibility to obtain the absorption coefficient spectrum of a sample by calculating the spectrum of the photocurrent

Figure 4.1: Schematic drawing of the Michelson interferometer, which is the main component of the Thermo Electron Nicolet 5700 FTIR spectrometer.

55 using an interferometer. The particular interferometer used throughout this work is the Thermo Electron Nicolet 5700 Fourier Transform Infrared (FTIR) spectrometer. To understand the working of this FTIR spectrometer, the Michelson interferometer is explained first, since this is the interferometer type on which the Nicolet 5700 is based. As can be seen in figure 4.1, the Michelson interferometer consists of two mutually perpendicular plane mirrors, one of which is fixed, while the other one can move along the axis perpendicular to its plane. In the middle of the interferometer, there is a beamsplitter, which splits the light from the source into two parts. One part is reflected towards the fixed mirror and the other transmitted part strikes the movable mirror. From both mirrors a beam is reflected, which returns to the beamsplitter, in which interference occurs. The beam returning to the source is ignored, because it is difficult to separate this beam from the source light, and only the output beam, which propagates in the direction perpendicular to the input beam, is used. Because of the interference of the beams reflected from the two mirrors, the intensity of the output beam depends on the optical path difference between the two interfering beams. For a better understanding, assume the light from the source to be monochromatic and the reflectance and transmittance of the beamsplitter to be both equal to 50%. The path difference between the two beams, or retardation, is calculated as

δ =−2 (OM OF ) , (4.18) where OM is the distance between the beamsplitter and the movable mirror and OF is the distance between the beamsplitter and the fixed mirror. Using equation 4.18, the phase difference between the interfering beams is

2πδ ϕ = , (4.19) λ in which λ is the wavelength of the source light. Now, the intensity of the output beam as a function of the retardation can be described as

121⎛⎞πδ II()δ =+=+ss()ννπνδ⎜⎟1cos I()( 1cos2 ), (4.20) 22⎝⎠λ

where Is(ν) is the intensity of the source as a function of the wavenumber ν [103]. In spectrometric measurements, there is no interest in the DC component, so this term in equation 4.20 can be ignored from now on. The resulting equation is also known as the interferogram:

1 II()δ = ()νπνδcos2 . (4.21) 2 s

To account for the influence of instrumental characteristics, such as the imperfection of the beamsplitter, absorption in optical parts of the FTIR

56 spectrometer, and the frequency dependence of the detector, an extra corrective factor has to be included:

1 IHI()δ ==()νν ()cos2 πνδν B () cos2 πνδ, (4.22) 2 s where B(ν) is the intensity of the source modified by instrumental and environmental characteristics. Notice now that I(δ) is in fact the cosine Fourier transform of B(ν) and that the spectrum B(ν) can be obtained by computing the inverse Fourier transform of I(δ). It is, however, more common to present the interferogram as a function of time and not as a function of retardation, because the movable mirror is moved at a constant velocity υ. To obtain a good resolution, it is recommended to use a low υ value; in the particular FTIR spectrometer used throughout this work, the lowest value that can be set is used, which is 0.1581 cm/s. If the movement is started with zero retardation, the following relation between retardation and the time t exists:

δ = 2υt . (4.23)

Substituting this in equation 4.22 gives:

It( ) =⋅= B(νπνυνπ) cos( 2 2 t) B( ) cos2 ftν , (4.24)

where fν is the modulation frequency of the light with wavenumber ν, which is scanned at velocity υ :

fν = 2υν . (4.25)

When the light of the source is not monochromatic, the measured interferogram is in fact a superposition of numerous interferograms corresponding to different wavenumbers, so the intensity of the output beam can be described by the following integral:

+∞ IB()δ = ∫ ()νπνδcos2 dν . (4.26) 0

From this, the spectrum B(ν) can be calculated by using an inverse Fourier transform:

+∞ +∞ BI()ν = ∫ ()δπνδcos2 dδ = 2cos2∫ I ()δ πνδ dδ . (4.27) −∞ 0

Just as in the case of CPM and DBP, this photocurrent spectrum is not absolute but relative, so it has to be calibrated to the absolute absorption coefficient spectrum measured by RT [61]. In principle, the spectrum can thus be obtained at an infinitely high resolution, but then the mirror would have to be moved over an infinitely long distance and the interferogram would have to be calculated with infinitesimally small intervals of retardation. In practice, the interferometer has a finite range over which it

57 can move the mirror and thus a finite retardation δmax. At the same time, the minimum retardation δmin is dictated by the finite sampling interval of the digitisation of the interferogram. Using the Nyquist–Shannon sampling theorem [104], it can be deduced that the best resolution that can be reached is

−1 Δ=ν δmax (4.28) and the maximum spectral range is obtained for

−1 Δ=ν δmin , (4.29) where Δν is the difference in wavenumber between two samples [105]. Typically, the resolution should be as high as possible; for the particular FTIR spectrometer used in this work, the maximum value that can be set is 32 cm-1.

4.5.2 Experimental setup The detection in FTPS differs from the detection in an alternating current (AC) setup like CPM, DBP, or PDS, where the photocurrent is modulated at a fixed frequency and detected by a lock-in amplifier, because in FTPS the photocurrent has the shape of an interferogram, dependent on the velocity of the moving mirror in figure 4.1. The induced photocurrent is now amplified with a Keithley Model 428-PROG current preamplifier. The amplified analogue signal is then digitised by an analogue-to-digital (A/D) converter and fed to a computer. The digitised time signal can now be transformed to the photocurrent spectrum by performing the inverse cosine Fourier transform, as described in equation 4.27 [61]. However, this photocurrent spectrum is relative and should be normalised to the absorption coefficient spectrum obtained from an RT measurement. To now give the reader an idea of what an FTPS system looks like, a picture of the particular system used throughout this work is displayed in figure 4.2. The heart of the FTIR spectrometer that is depicted in figure 4.1 is not visible in figure 4.2, since the interferometer and the beamsplitter have to be conserved in a nitrogen environment and thus with the lid of the spectrometer closed during a measurement. The modulated light exits the FTIR spectrometer on the left side in figure 4.2, and then enters a hardboard black box which prevents stray light from illuminating the sample and interfering with the FTPS measurement. Inside the black box, the light strikes an elliptically concave Al mirror at an acute angle and is reflected in the plane parallel to the table. The reflected beam is then focused onto the sample which is attached to a Zn- coated steel plate by a pair of magnets. Both the sample holder and the mirror are vertically mounted onto an optical breadboard to diminish the influence of mechanical vibrations on the measurement. As said in the beginning of this section, in FTPS a Nicolet 5700 FTIR spectrometer is used to modulate the source light. This spectrometer is equipped with a choice of beamsplitters: calcium fluoride (CaF2), potassium bromide (KBr), and quartz (SiO2). For FTPS, the most suitable of these three materials is CaF2, since it has the highest transmittance

Figure 4.2: The FTPS measurement setup used throughout this work.

(i.e. the lowest absorption) over a wide range of wavelengths: ~92% between 0.4 μm and 6 μm [106]. A white light source (tungsten 20 W halogen) is used to obtain the absorption coefficient spectrum in the infrared as well as in the visible range of wavelengths, or to be more precise from 2,500 nm to 637 nm, which corresponds to 4,000 cm-1 – 15,700 cm-1 or 0.50 eV – 1.95 eV (remember equations 4.20 and 4.6). The modulation frequencies thus range from 1,200 Hz to 4,710 Hz (use equation 4.25 with υ = 0.1581 cm/s). The lower bound of this wavelength range is formed by the wavelength of the red helium-neon (HeNe) laser (632.8 nm) which is in line with the white light beam, so the FTIR spectrometer can measure and control the position of the moving mirror. Measuring modulation frequencies larger than the modulation frequency of the laser (4,740 Hz) is thus not possible, since this will result in aliasing, meaning that the light signal can no longer be demodulated unambiguously. The upper bound of the wavelength range is determined by the material: above 2,500 nm, the absorption is generally so low that the resulting FTPS signal becomes very noisy, because for such low photon energies (below 0.5 eV) the majority of the photo-generated electron-hole pairs are not involved in transitions to the extended states and thus do not contribute to the photocurrent. Measuring in that wavelength area is therefore not considered useful and should be avoided, since it only results in a longer measurement time. The detector in figure 4.1 is the sample under investigation. When the sample is a film, the detection is performed by applying a voltage

59 from a stable voltage source (Keithley Model 2410) to the electrodes that are deposited on top of the film to create an electric field that separates the photo-generated electron-hole pairs. In this work, the distance between the electrodes is 0.5 mm and the applied voltage is 1,000 V for all measured films on glass. For solar cells, it is not necessary to apply an external voltage, as the charge carriers are already separated by the internal electric field (see section 3.5.1). The resulting FTPS signal then has to be normalised to the background FTIR signal from a spectrally independent detector, like a pyrodetector of deuterated triglycerine sulphate (DTGS) or a calibrated silicon photodiode, to correct for the spectrum of the lamp and the optical characteristics of the spectrometer. In case of the silicon photodiode, the signal is already proportional to the number of photons hitting the detector, but when a DTGS pyrodetector is used, the signal has to be divided by the photon energy to conserve proportionality to the number of photons hitting the detector. In this work, the latter method is used, since the sensitivity of the Si photodiode is very low below 1.1 eV (remember figure 3.4a), making it impossible to perform a proper background measurement for the low-energy range with the Si photodiode. Further, corrections on the normalised FTPS signal are made for the frequency dependence of both the DTGS detector and the a-Si:H detector [107], which are determined by the modulation frequency response at the used FTIR mirror velocity of 0.1581 cm/s. These corrections are required because different detectors are used for the FTPS measurement and the background measurement. The relative frequency responses are obtained by performing a background measurement and an FTPS measurement of a sample at different FTIR mirror velocity settings. The measurement signals recorded with different scan velocities can be plotted versus the modulation frequency, and after a normalisation and fitting procedure is performed, the different correction functions can be approximated, e.g. by a quintic polynomial. This fitting procedure is extensively described in [108] and will not be further discussed here. Finally, it should be noted that the relative frequency responses of an a-Si:H solar cell absorber layer and an a-Si:H film are not equal [108]. As stated earlier in this subsection, no photons with wavelengths below the wavelength of the red laser should strike the sample to avoid aliasing. For this reason, an optical filter should always be used that cuts off all wavelengths below the wavelength of the laser. In the used FTIR spectrometer, this filter has a cut-off wavelength of 645 nm. To increase the dynamic range, another four optical filters with increasing cut-off wavelengths (695 nm, 780 nm, 850 nm, and 1050 nm) are used to measure different parts of the spectrum. Note that the filter with the highest cut-off wavelength is no regular optical filter, but a 2 mm thick polished c-Si wafer. For convenience purposes, the optical filters are mounted on filter wheels which are located inside the spectrometer, where they can be controlled by software. By performing an FTPS measurement with an optical filter with a higher cut-off wavelength, an increasing part of the spectrum of the lamp is gradually cut off. This means that the absorption coefficient for the lower photon energies, where the material is less absorbing, can be more accurately obtained. When measuring in this manner instead of only measuring once with the filter with a cut-off wavelength of 645 nm, the dynamic range of the A/D converter forms a lesser limitation to the accuracy of the obtained absorption coefficient

60 spectrum. Because an FTPS measurement of one sample thus requires five measurements with the different optical filters, more measurement time is needed per sample, but this is still limited to several minutes. The software that is used to operate the FTIR spectrometer and start an FTPS measurement is Thermo Electron’s OMNIC program version 7.1a. By using the software, several settings of the FTIR spectrometer can be controlled, such as the optical filters, the resolution, the wavenumber range to be measured, and the number of scans. In this context, the number of scans represents the amount of identical measurements over which OMNIC averages to increase the signal-to-noise ratio of the FTPS signal. The number of scans has to be determined empirically for each sample and for each measurement with one of the optical filters. In practice, this means that the number of scans is doubled when the recorded spectrum is considered too noisy. An acceptable start value for the measurement with the filter with a cut-off wavelength of 645 nm has been found to be 32 scans, which corresponds to a measurement time of 23 seconds. When the cut-off wavelength of the used filter increases, the intensity of the light spot that illuminates the sample decreases, which causes the signal-to-noise ratio of the FTPS signal to decrease. This makes it necessary to increase the number of scans. Typically, using more than 1024 scans is not considered useful, since the signal-to-noise ratio will no longer significantly improve. For some samples, it can occur that no signal remains when the cut-off wavelength of the optical filter is increased beyond a certain point. In that case, the measurement procedure is best aborted and less than five measured spectra are then used to form the relative photocurrent spectrum. The output of OMNIC – the five spectra measured with the different optical filters – can be stored in comma-separated value files, making it possible to further process the data to obtain the relative photocurrent spectrum. The stored intensity and wavenumber data (these correspond to B and ν in equation 4.27) are processed in a MATLAB script file, which performs all of the calculations and signal corrections described in this subsection and is capable of processing the measurement data for multiple samples in one run. Further details of the MATLAB script can be found in Appendix A. The output of the script is a relative photocurrent spectrum for each of the samples defined in the input matrix of the script. As stated before, this spectrum now has to be connected to the spectrum measured by RT to obtain the absolute absorption coefficient spectrum for photon energies above and below the band gap. Typically, the two spectra are connected at an energy value of 1.82 eV, since for higher photon energies the relative photocurrent spectrum starts to fall off due to a lower transmittance of the optical filter with a cut-off wavelength of 645 nm. In order to connect the two spectra, the OPTA program is used, as will be further discussed in section 4.6.

4.5.3 Improved experimental setup The FTPS measurement system that has been described in the previous subsection, has been successfully used in [108] and in this work to obtain the results presented in the following chapters. It appeared, however, that some aspects of the system were not optimal and therefore several

61 improvements have been implemented. These improvements will be discussed in this subsection. One of the problems with the above-described FTPS system is the way the sample is fixed to the sample holder. Because the sample is mounted vertically, the magnets always allow for some movement of the sample when the sample holder is exposed to large mechanical vibrations. For the same reason, the measurement pins that are used to contact the electrodes of the sample can move when they are exposed to mechanical vibrations, since they are also fixed to the sample holder by magnets. In the worst case, this means that the measurement pins can touch each other, e.g. when somebody accidentally hits the table on which the system is resting, causing a short-circuit in the measurement system. When a film is measured, the voltage of 1,000 V that is applied to the electrodes of the sample is then across the input of the current amplifier, which has fatal consequences for the amplifier. To avoid the costly repairs of the amplifier and to make it easier to load the sample, a new sample holder has been designed. The new sample holder is mounted horizontally, instead of vertically, to prevent sliding of the sample along the sample holder during mechanical vibrations. For the same reason, the measurement pins with magnetic mounts have been replaced by

Figure 4.3: Configuration of the mirror and the sample holder on the inside of the hardboard black box in the original FTPS system.

62 measurement pins that are firmly mounted onto the sample holder by means of screws. A picture with both the old and the new sample holder with an a-Si:H film on glass attached to it can be seen respectively in figure 4.3 and figure 4.4. With the new sample holder, the light now has to be reflected perpendicularly upwards, which means that a box taller than the hardboard one is required to keep out stray light. Since a new box had to be custom-made by the faculty’s mechanical workshop Dienst Elektronische en Mechanische Ontwikkeling (DEMO) anyway, a closer look has been taken to the design, to see whether more adaptations with respect to the old hardboard box were necessary. Firstly, the sliding door of the hardboard box through which the sample has to be loaded in the

Figure 4.4: Configuration of the mirror and the sample holder on the inside of the aluminium box in the improved FTPS system. The voltage source is not visible in the picture because it is placed under the table on which the system is resting to keep a safe distance between the voltage source and the current amplifier.

63 old system measures only 25 cm by 25 cm, so it is not very easy to place the sample in the focal point of the light and fix it to the sample holder with the magnets. For the new box, an easier access to the sample holder was therefore considered necessary and two fully detachable aluminium lids have been added to the new box. Since the sample holder is close to the top lid, only the screws fixing this lid have to be undone when loading a sample. The other lid can be removed when e.g. the alignment of the mirror has to be adjusted. To diminish the influence of internal reflections, the inside of the box is covered with a black opaque coating. The FTPS system with the hardboard box frequently suffered from noise in the interferogram. Empirically, it has been determined that this is caused by electromagnetic waves that interfere with the modulation frequencies of the signal or with signal frequencies present in the electronics of e.g. the current amplifier. The electromagnetic waves interfering with the modulation frequencies of the light coming out of the FTIR spectrometer are likely to be radiated by a series of pumps that is in the vicinity of the FTPS system. Further, the voltage source that is used during the FTPS measurement on an individual film radiates magnetic waves which adversely influence the performance of the current amplifier. Therefore, the two should be placed apart and not on top of each other. More importantly, in the old system, the hardboard box only prevents stray light from interfering with the modulated light used in an FTPS measurement. Electromagnetic radiation with lower frequencies is not properly shielded, which is the reason why the new box is made of aluminium. Before, the sample holder together with the metal optical breadboard effectively worked as a (poor) receiver of electromagnetic signals and when an aluminium box is placed on top of the breadboard, the “antenna” becomes even larger. Therefore, it is required to have a proper grounding of these metal components. The metal box with the lids, the breadboard, and the sample holder are thus well connected to keep them at the same potential. The grounding is then performed by the outer conductors of the coaxial cables, which connect the measurement pins to the voltage source and the current amplifier. To transport the photocurrent, only the inner conductor of the cable is used, so the outer conductor can be used freely to ground the metal components of the system through the ground of the amplifier. Note that no ground loop is created, since both the amplifier and voltage source are connected to the same ground. The resulting newly designed aluminium box is illustrated in figure 4.4. In the new system, an Ag mirror is preferred over an Al mirror, since Ag has a wavelength-independent reflectance for the investigated wavelength range, which is not the case for Al. The different reflectance curves of Al and Ag can be seen in figure 4.5a. To avoid having to make a correction for the wavelength-dependent reflectance of Al, it is better to use an Ag mirror. This correction function can be obtained from two FTPS measurements on a μc-Si:H solar cell using an Al mirror and an Ag mirror. The reason for using a μc-Si:H sample rather than an a-Si:H sample here, is because μc-Si:H is more resistant against photo-induced degradation than a-Si:H (see section 3.4). This ensures that the quality of the measured material does not significantly change in between the two FTPS measurements. The difference in reflectance between the two mirrors for which the correction has to be made can be calculated by dividing the α

(a)

1.05

1.00

0.95

(b) 0.90

0.85

0.80

0.75 normalised reflectance Al (-) 0.70 600 700 800 900 1000 1100 1200 wavelength (nm)

Figure 4.5: (a) Typical reflectance spectra for Al and Ag (graphs taken from [109]) and (b) for Al normalised to Ag as obtained from FTPS measurements on a μc-Si:H sample supplied by the University of Neuchâtel.

spectra obtained from FTPS measurements using the two different mirrors. The resulting reflectance of the Al mirror normalised to the reflectance of the Ag mirror is depicted in figure 4.5b. Note that for wavelengths below 670 nm, the normalised reflectance of the Al mirror is exactly 1, since in this wavelength range, the α values obtained from one and the same RT measurement are used. Because in the new system the sample holder is mounted horizontally, the light has to be reflected upwards by a mirror under an angle of 90°. The old mirror is not very suitable for such a large angle of incidence, because an elliptically concave mirror deforms the light significantly. To get a one-to-one image of the modulated light coming out of the FTIR spectrometer, it is better to use a parabolic off-axis mirror, since this type of mirror does result in a non-deformed light spot on the sample. The reason why the deformation of the light spot should be as small as possible lies in the fact that the focused light consists of one bright main spot that contains the modulated light frequencies and two secondary spots next to the main spot. These secondary spots result from the so-called ghosting effect in the beamsplitter: since the beamsplitter has a finite thickness, reflection and transmission occur both on the front

65 and the back side of the beamsplitter material, resulting in secondary light beams at the exit slit of the spectrometer. Moreover, these secondary beams have a poorly defined spectrum and should therefore not illuminate the sample to be able to correctly demodulate the light that is incident on the sample. When an elliptical mirror is used to reflect the light, the main and secondary spots are closer to each other and more narrow than when an off-axis mirror is used. Thus, when using an off-axis mirror, it is easier to prevent the secondary light spots from illuminating the sample. In the new system, this is done by placing a 10 mm by 2.5 mm slit over the sample. Using these slit dimensions, the secondary spots are blocked and only the main spot can illuminate the sample. For illustrative purposes, pictures of the modulated light reflected by the elliptical mirror and the off-axis mirror are depicted in figure 4.6, as well as a picture of the reduced spot when the slit is used.

(a) (b) (c)

Figure 4.6: Projection of the modulated light onto the new sample holder when using (a) an elliptically concave mirror, (b) a parabolic off-axis mirror, (c) a parabolic off-axis mirror in combination with a slit. All three pictures are depicted on the same scale. The diameter of the circular hole in the sample holder over which a sample is placed is 20 mm.

Because the elliptical mirror deforms the light, the main and secondary spots are very close to each other in figure 4.6a, making it difficult to properly block the secondary spots with a slit. When the off- axis mirror is used, the main and secondary spots are further apart and wider (see figure 4.6b), making it possible to define a rectangular part of the main spot where the frequency components of the light are well- defined. When a slit is used, only this rectangular part of the original main spot can illuminate the sample, as can be seen in figure 4.6c. Simply using a very narrow slit to eliminate the secondary spots will not help, because this will result in a much lower intensity of the light that illuminates the sample, which drastically reduces the signal-to-noise ratio of the FTPS signal and increases the number of required scans during a measurement. To check the influence of using a slit on an FTPS measurement, and thus on the α spectrum, comparative measurements (with and without the slit) are performed with the μc-Si:H solar cell. The

105 4 new mirror no slit 10 new mirror slit 103 102

) 1

-1 10 100 (cm α 10-1 10-2 10-3 10-4 10-5 0.60.81.01.21.41.61.82.02.22.4 energy (eV)

Figure 4.7: Absorption coefficient spectra obtained from FTPS on a μc- Si:H solar cell with and without using a slit that prevents the secondary light spots from illuminating the sample.

resulting α spectra are illustrated in figure 4.7. When the slit is placed in front of the sample, this results in an α spectrum that is close to the α spectrum obtained from a measurement without using the slit. However, using the slit results in a slightly higher α approximately below 1.6 eV. This difference in α is ascribed to a reduced intensity of photons with energies approaching 1.82 eV, which is the energy where the photocurrent spectra obtained from FTPS and the α spectrum obtained from RT are connected (see section 4.5.2). When the slit is used, the relative photocurrent spectrum falls off for the higher photon energies, causing α to increase for the lower photon energies when the relative photocurrent spectrum is connected to the absolute α spectrum. When the off-axis mirror is used, only a small part of the secondary spots illuminates the sample, so using a slit does not greatly influence the shape of the α spectrum, as is also clear from figure 4.7. Still, when using the slit, it is certain that only the main spot illuminates the sample and, therefore, it is strongly recommended to use it.

4.6 Calculating the absorption coefficient spectrum As stated earlier, the photocurrent spectra obtained from FTPS, DBP, or CPM should be normalised to the absolute absorption coefficient spectrum obtained from an RT measurement. In this thesis, the required normalisation is performed using the OPTA program. The photocurrent spectrum could be connected to the absolute absorption coefficient spectrum by properly scaling the photocurrent spectrum by using e.g. MATLAB, but this method is not recommended, as it does not account for interference fringes in the photocurrent spectrum. Especially for this reason, OPTA is used because it contains an optical model (see section 4.1) that can reduce the interference fringes present in the photocurrent spectrum. These interference fringes result from multiple reflections inside

67 the measured film [110] (or absorber layer, in case of a solar cell) and greatly impede the determination of the defect density from the absorption coefficient spectrum (see section 3.3.2). Further, interference fringes make it difficult to smoothly connect the two spectra. Therefore, to obtain a more reliable estimate of Nd, it is required to reduce the interference fringes. This is commonly done by simply smoothing the α curve, but because a smoothing method has no physical foundation, it is not recommended. A better method is to use an optical model in which internal reflections are accounted for, like the model included in OPTA. To reduce the interference fringes with OPTA, the value for the thickness of the film in OPTA is adjusted until the relative photocurrent spectrum obtained from FTPS and the absolute α spectrum obtained from RT can be smoothly connected. When DBP is used instead of FTPS, OPTA is used in the same way to connect the relative photocurrent spectrum obtained from DBP to the absolute α spectrum obtained from RT. Another way of reducing the interference fringes is by using the so- called Ritter-Weiser method that uses the absorbance-to-transmittance ratio A/T to estimate the α spectrum. Since both A and T show equally shaped interference fringes for the same photon energies, the fringes are no longer present in A/T [111]. Recently, it has been proposed to use this approach by performing two different FTPS measurements on the same sample: firstly in the normal FTPS configuration and secondly with another piece of the same sample placed in front of the measured sample to use it as an optical filter. The first measurement is thus proportional to A, while the second measurement is proportional to A·T. The ratio A/T is then easily calculated and indeed results in an interference-free α spectrum [112]. It is has been attempted to use this method for a-Si:H films, but when measuring with the additional sample as an optical filter, a large fraction of the light is already absorbed in the first sample, resulting in a very small and thus noisy FTPS signal. In fact, using the spectrum that is proportional to A·T to calculate the interference-free α spectrum resulted in an increased uncertainty of the α values. Further, two FTPS measurements instead of one are required for each sample which increases the total measurement time per sample. Considering this, it has been chosen to use OPTA to reduce the interference fringes and not the Ritter-Weiser method. The drawback of using OPTA is that there is some uncertainty on the chosen value for the thickness, since the smooth connection between the relative photocurrent spectrum and the absolute α spectrum is graphically determined, i.e. by hand. Further, the scaling of the relative photocurrent spectrum to the absolute α spectrum is also performed graphically. This procedure of connecting the spectra, therefore, introduces an error in the parameters that are obtained from the connected spectrum, such as Nd, ET, EK, and EU (see sections 3.3.2 and 3.3.3). When the overlap between the two spectra is large enough, so a smooth connection can easily be made, the introduced error is rather small. This holds for DBP / RT, where the overlap is typically 0.3 eV. For FTPS / RT, however, the overlap is typically not even 0.1 eV, because 1.85 eV is the highest photon energy value in the relative photocurrent spectrum that can be used, while 1.8 eV is the lowest usable energy value in the absolute α spectrum. To increase the energy overlap between the two spectra, a laser with a lower wavelength (e.g. a green laser) could be used in the FTIR spectrometer,

68 so the relative photocurrent spectrum can extend to higher photon energies, making it easier to connect the two spectra. Unfortunately, such a spectrometer was not available when this work was compiled, so the reader should be aware of some uncertainty in the values of Nd, ET, EK, and EU presented in the following chapters.

4.7 Comparison of FTPS with PDS, CPM, and DBP The most important advantage of FTPS over DBP, CPM, and PDS is the strongly reduced measurement time: several minutes instead of hours. This is because, in FTPS, all modulated wavelengths of the light illuminate the sample simultaneously, while in the other methods, a monochromator is used to select one wavelength at the time. Since, in FTPS, an inverse Fourier transform is used to calculate the photocurrent spectrum from the measured data, there is no need to step through the whole wavelength range of interest. In addition to this saving of time, FTPS is more sensitive to low photon energies than CPM and DBP. In the latter two cases, a sub- band gap absorption as low as 0.8 eV can be measured, whereas, in FTPS, this is further decreased to 0.5 eV. Moreover, FTPS measurements on μc-Si:H films have been reported to result in a full dynamical range of α(E) exceeding nine orders of magnitude [107], which can also be seen from the α spectra determined from FTPS measurement that are presented in the following chapters. The difference in sensitivity between FTPS and PDS is less distinct, but PDS tends to overestimate the α for low photon energies because of its sensitivity to surface states, which is not the case for FTPS. A disadvantage of FTPS with respect to the other three methods is that a complete FTPS system is relatively expensive. This is mainly due to the FTIR spectrometer, which typically costs several tens of thousands of euros, depending on the type and the minimum velocity at which the mirror in the spectrometer can be moved. Namely, to obtain a low uncertainty in the absorption coefficient data, the movement of the mirror has to be controlled very accurately. Further, in the calculation of the absorption coefficient in section 4.5.1, it is assumed that the reflectance and transmittance of the beamsplitter are both equal to 50%. Practically speaking, it is very difficult to find a material which has this property for a wide range of wavelengths and maintains the same reflectance and transmittance over a long period of time. To keep the hereby introduced error acceptably small, the price of the beamsplitter can be as high as a few thousand euros. Concluding, it can be said that CPM, PDS, DBP, and FTPS are complementary methods for obtaining a reliable absorption coefficient spectrum and for obtaining additional information about the electronic properties of the material under investigation. When all advantages and disadvantages of each of these measurement methods are taken into account, it should now be clear that each method has its limitations, which means that neither of these methods is the best in general. However, for the structural optimisation of the deposition parameters of an a-Si:H solar cell absorber layer, FTPS is a very attractive method to obtain the α spectrum, because of its short measurement times and high sensitivity.

5 Optimising a-Si:H films and solar cell absorber layers As has been discussed in section 3.3, the absorption coefficient spectrum can be used to obtain several parameters that contain information about the quality of the material, such as the defect density, the Tauc gap, the Klazes gap, and the Urbach energy. Since a-Si:H is a promising photovoltaic material for use in low-cost solar cells, especially in the micromorph configuration (see sections 2.4 and 3.1), a structured optimisation of the deposition parameters of this material has been performed by depositing series of a-Si:H films and solar cells. To verify the quality of the deposited material, the absorption coefficient spectrum has been obtained for each sample from RT, DBP, and FTPS measurements (see respectively section 4.1, 4.4, and 4.5). In section 5.1, the optimisation procedure of an a-Si:H layer (deposited individually on glass and as an absorber layer in a solar cell) is discussed, followed by the results from the variation of the different deposition parameters in the remaining sections of this chapter. In sections 5.2 to 5.5, respectively, the deposition pressure, the rf-power, the silane flow, and the substrate temperature have been varied, while keeping the other deposition parameters constant. The quality of the samples are then compared within each series and consequently an optimal set of deposition parameters can be deduced, initially neglecting the effect of prolonged light soaking.

5.1 Optimisation procedure

5.1.1 Introduction As stated earlier in this report, a-Si:H is a promising material for use in low-cost solar cells, especially in the so-called micromorph configuration, which consists of an a-Si:H top cell and a μc-Si:H bottom cell (see section 3.1 and [74]). This micromorph silicon solar cell has the potential to achieve a stabilised efficiency of 15% [113],[114]. So far an initial efficiency of 14.1% [115] and stabilised efficiencies between 10% and 12% [80],[116],[117] have been reported. The difference in initial and stabilised efficiencies is caused by the photo-induced degradation of a-Si:H, also known as the Staebler-Wronski effect (see sections 2.4, 2.5.2, and 3.4 and [87]). It has been shown that hydrogen dilution of the silane source gas during the rf-PECVD deposition (see section 3.5.2) of the a-Si:H absorber layer can suppress the Staebler-Wronski effect (see section 3.2 and [93],[94]). As has been discussed in section 3.2, the condition of a sufficient hydrogen dilution of the silane source gas during the rf-PECVD deposition results in the so-called protocrystalline growth regime. The amorphous silicon grown under these conditions is referred to as protocrystalline silicon. The hydrogen dilution also induces a phase change from pc-Si:H to mixed a-Si:H / μc-Si:H and finally to μc-Si:H when the film is grown to a sufficient thickness [76]. This result has been verified by means of

Transmission Electron Microscopy (TEM) by the investigation of Si:H films deposited at different hydrogen dilutions (see figure 3.3 and [77]). The thickness of the protocrystalline incubation layer is strongly related to the hydrogen dilution of the silane source gas and decreases rapidly for increasing hydrogen dilution [76],[77],[118]. Therefore, the minimum required thickness of the absorber layer in a solar cell (typically

300 nm) poses an upper limit on the dilution ratio R = [H2]/[SiH4]. In summary, the hydrogen dilution ratio for growing a fully protocrystalline absorber layer has to be chosen high enough to yield stable material, yet low enough to avoid the formation of mixed-phase material. A moderate hydrogen dilution ratio of R = 20 is chosen in this work, as this will significantly influence the material properties, but still allows for a relatively large range of deposition conditions for which the phase transition does not occur. Methods to avoid the phase transition during the protocrystalline growth of silicon, such as dilution profiling [119] or layer- by-layer deposition [120], are not considered here; all films and absorber layers mentioned in this work are deposited in a one-step process, meaning that the hydrogen dilution ratio is not changed during the deposition. Series of Si:H films and solar cells with corresponding absorber layers deposited at different pressures, rf-powers, silane flows, and substrate temperatures are investigated in the following four sections of this chapter in a structured way, in order to determine the influence of these deposition parameters on the quality of the deposited material. The stability of the four series of films and solar cell absorber layers during light soaking will be investigated respectively in sections 6.2 – 6.5. To quantify the sub-band gap absorption coefficient spectrum of the films and the corresponding absorber layers, FTPS (see section 4.5) and DBP (see section 4.4) are used in combination with RT (see section 4.1) measurements. From the obtained absorption coefficient spectrum, the defect density, the Tauc gap, the Klazes gap, and the Urbach energy of the deposited material can be obtained (see sections 3.3.2 and 3.3.3). To monitor the behaviour of the hydrogen-diluted absorber material during light soaking, FTPS is used to characterise the time evolution of the defect density for both silicon films and solar cell absorber layers. During the degradation experiment that will be the main topic of chapter 6, the external parameters of the solar cells with the diluted absorber layers are monitored by means of repeated JV measurements (see section 3.5.3) and compared to the external parameters of a reference solar cell with an undiluted absorber layer to verify the increased stability of the hydrogen- diluted material. In sections 5.2 – 5.5, only the results from JV measurements on the solar cells in the initial state, i.e. before light soaking, will be presented.

5.1.2 Deposition conditions of films and solar cells All individual films that will be discussed in the remainder of this report are deposited on a very transparent piece of glass (Corning Eagle 2000). As stated earlier in this subsection, a structured optimisation of a-Si:H films and absorber layers is performed by varying one deposition parameter, while keeping the other deposition parameters constant. This

72 means that a reference material is required. The reference R = 20 material is deposited by means of rf-PECVD (13.56 MHz) using the following conditions: a deposition pressure of 2.00 mbar, an rf-power of 4 W, a silane flow of 5 sccm, and a substrate temperature of 180 °C. Similarly, an undiluted reference R = 0 material is required to check whether the SWE in the R = 20 material is indeed less pronounced than in the R = 0 material. This reference R = 0 material is deposited using the following conditions: a deposition pressure of 0.70 mbar, an rf-power of 4 W, a silane flow of 40 sccm, and a substrate temperature of 180 °C. To be able to compare the quality of the samples, and the values for Jsc (see section 3.5.3) in particular, the thicknesses of all investigated films and solar cell absorber layers are kept equal: 300 nm (±30 nm). To compare the material quality differences in films and solar cell absorber layers, identical deposition parameters are used for the deposition of both the individual films on glass and the corresponding solar cell absorber layers. The deposition conditions of the other layers in the solar cells are kept constant at the values stated in table 5.1. For the sake of completeness, the deposition conditions of both the R = 0 and R = 20 absorber layers of the reference solar cells have been included in the table as well.

Layer SiH4 CH4 B2H6 PH3 H2 p P T Time [sccm] [sccm] [sccm] [sccm] [sccm] [mbar] [W] [°C] p 20 45 2 0 0 0.7 4.5 180 45s buffer 1.6 3.7 0 0 200 2.6 6.0 180 4m i (R = 0) 40 0 0 0 0 0.7 4.0 180 25m27 i (R = 20) 5 0 0 0 100 2.0 4.0 180 ~80m n 40 0 0 11 0 0.6 4.0 180 4m39

Table 5.1: Deposition conditions used for depositing the different layers of the investigated solar cells by means of rf-PECVD. The deposition conditions of the individual films on glass are equal to the conditions that are used for the deposition of the i-layers in the solar cells.

Using these reference parameters, several deposition parameters of the films on glass and the i-layers can now be varied to optimise the deposition conditions of this material at R = 20. The deposition pressure is varied between 1.35 mbar and 2.60 mbar, the rf-power range is 4 W –

16 W, the SiH4 flow is varied between 1 sccm and 10 sccm (the H2 flow is varied accordingly to keep R = 20), and finally the substrate temperature is varied between 150 °C and 200 °C. Note that the deposition time of the absorber layer that is required to grow a layer of 300 nm is dependent on the deposition conditions. For most conditions considered here, the deposition time of the R = 20 films and i-layers is ~80 minutes, whereas the deposition time decreases linearly to ~30 minutes when the rf-power is increased from 4 W to 16 W. The substrate of all solar cells discussed in the remainder of this report is the so-called Asahi U-type, which consists of Corning Eagle 2000 covered with a textured TCO layer that serves as the front contact of the solar cell. The further structure of the solar cells is as follows: Asahi U-type / p-type a-SiC:H layer (10 nm) / a-SiC:H buffer layer (~5 nm) /

(a) (b)

Figure 5.1: The typical structure of (a) the individual films on glass and (b) the p-i-n solar cells that are investigated in this report. Note that the buffer layer is not depicted in the p-i-n structure. Graphs are adapted from [57].

intrinsic a-Si:H absorber layer (~300 nm) / n-type a-Si:H layer (20 nm) / aluminium back contact (300 nm). The reference solar cells with the R = 0 and R = 20 absorber layers have been deposited also with the following back contact: Ag (100 nm) / Al (200 nm). The reason for using this different back contact configuration is that AgAl has a higher reflectance than Al, resulting in a higher value for Jsc and thus also in a higher value for η. However, solar cells with this type of back contact show a larger relative degradation after light soaking. To compare the influence of the different back contact configurations on the performance of the solar cells, the reference solar cells with both AgAl and Al back contacts have been included in the light soaking experiment that will be discussed in chapter 6. For illustrative purposes, schematic representations of the films on glass and the typical p-i-n structure that is used for all solar cells discussed throughout this work are depicted in figure 5.1. After the deposition of a solar cell with an Al back contact, the solar cell is annealed in an oven at 130 °C for 30 minutes to eliminate possible barriers between the contacts and the p-i-n structure at the interfaces, i.e. to improve the contact. Note that this additional annealing step is not performed for solar cells with an AgAl back contact, since this would lead to intermixing of the two metals, which results in a strongly reduced reflection from the back contact.

5.2 Variation of the deposition pressure To investigate the influence of the deposition pressure on the properties of the absorber layer, a systematic study is performed of the effect of the deposition pressure on the quality of the deposited material. For this reason, both films and absorber layers have been deposited with pressures varying between 1.35 mbar and 2.60 mbar, while keeping the other deposition conditions constant (see section 5.1). The absorption coefficient spectra obtained from FTPS and RT measurements on the Si:H films deposited at different pressures are depicted in figure 5.2.

105 104 103 102

) 1

-1 10 1.35 mbar 100 (cm 1.57 mbar α 10-1 1.79 mbar -2 2.00 mbar 10 2.20 mbar 10-3 2.40 mbar -4 2.60 mbar 10 10-5 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 energy (eV)

Figure 5.2: Absorption coefficient spectra obtained from FTPS and RT on silicon films deposited at R = 20 and varying pressures.

A differently shaped absorption coefficient spectrum is observed for the films deposited at pressures below 2.00 mbar, indicating a phase transition from the amorphous to the microcrystalline phase for decreasing pressure. This phase transition is confirmed by Raman measurements on the same films [118]. To verify that these α spectra obtained from FTPS and RT are correct, DBP measurements on the same films have been performed. The α spectra obtained from DBP and RT are depicted in figure 5.3. The photocurrent spectra obtained from DBP and FTPS have been scaled to the absolute α spectrum from the same RT measurement, so for the super- band gap region, the α spectra are identical in both figures. Further, in the sub-band gap region above ~0.9 eV, no significant difference between the two series of α spectra can be seen. Below this energy, however, the sensitivity of DBP decreases and the α values are more determined by the noise floor and the time constant of the lock-in amplifier rather than by the photocurrent. This is further confirmed by the increasing α values below ~0.9 eV in figure 5.3. FTPS does not suffer from this sensitivity problem and the α spectra obtained from FTPS / RT show decreasing trends for photon energies as low as 0.6 eV. Below ~0.9 eV, the uncertainty in the α values does increase, because of the very small

105

104

103

2 ) 10 -1 1.35 mbar 101 (cm 1.57 mbar α 100 1.79 mbar 2.00 mbar 10-1 2.20 mbar 2.40 mbar 10-2 2.60 mbar

10-3 0.81.01.21.41.61.82.02.22.4 energy (eV)

Figure 5.3: Absorption coefficient spectra obtained from DBP and RT on silicon films deposited at R = 20 and varying pressures. The investigated films are equal to the films of which the absorption coefficient spectra are depicted in figure 5.2.

photocurrent for those photon energies, but for decreasing photon energy, a clear decreasing trend is still visible in the α spectra. In summary, it can be said that FTPS / RT and DBP / RT on films give very similar α spectra for photon energies above ~0.9 eV; for lower energies, only FTPS is sensitive enough to measure accurately. The required measurement time for one film with FTPS is typically between 30 and 50 minutes; the low end of this range can be reached by decreasing the number of scans for each of the five measurements of which an FTPS measurement consists (especially for the measurements with the optical filters with the highest cut-off wavelengths for which the photocurrent is the smallest; see section 4.5.2). However, to obtain smoother α spectra – and thus a more accurate value for e.g. the defect density – it is not recommended to use little scans. The measurement time for one film with DBP is typically 30 minutes, but for films with a poor conductivity or a high defect density, this can increase to 50 minutes as well, since for the low-energy range, the lock-in amplifier has increasingly more difficulties to measure accurately. Note that these measurement times are typical for the films discussed in this thesis; for FTPS measurements on films of different materials than a-Si:H or μc-Si:H, the measurement times can be very different. As stated earlier, the deposition conditions that have been used to deposit the films on glass are also used for depositing the i-layer in a solar cell. The α spectra resulting from FTPS / RT measurements on the solar cells with absorber layers deposited at different pressures, corresponding to the aforementioned films on glass, are depicted in figure 5.4. To scale the photocurrent spectra obtained from FTPS to the absolute α spectra, the RT measurements performed on the individual films are used again in the calculation of the α spectra of the absorber layers, as it is not possible to perform an RT measurement on an individual i-layer in a solar cell.

105 104 103 102 1

) 10 -1 100 1.35 mbar -1 (cm 10 1.57 mbar α -2 1.79 mbar 10 2.00 mbar (Al) 10-3 2.00 mbar (AgAl) 10-4 2.20 mbar -5 2.40 mbar 10 2.60 mbar 10-6 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 energy (eV)

Figure 5.4: Absorption coefficient spectra obtained from FTPS / RT on the solar cells with absorber layers deposited at R = 20 and varying pressures corresponding to the aforementioned films on glass.

Note that no comparative DBP measurements on the solar cells could be performed because of the physical limitations of the available DBP system. The phase transition for decreasing pressure that was observed for films does not appear in the solar cell absorber layers, since all α spectra now have a similar shape. When closely inspecting figure 5.4, it can be seen, however, that for photon energies above 1.8 eV, the α values of the absorber layer deposited at 1.35 mbar are somewhat lower than α values of the other absorber layers. This can indicate that the material has a certain crystalline fraction, as is the case for the film deposited at 1.35 mbar, but for the corresponding absorber layer this is not the case. The only reason for the lower α values in the energy range above 1.8 eV is that the α values obtained from the RT measurement on the corresponding film have been used again to calculate the α spectrum of the absorber layer deposited at 1.35 mbar. The observed phase difference between the α spectra of the films and the corresponding absorber layers is due to a strong substrate dependence during the Si:H growth from hydrogen-diluted silane [120]: the films are grown on glass, while the absorber layer in a solar cell is grown on a textured a-SiC:H layer. Note that for the absorber layer deposited at 2.00 mbar, the two different back contact configurations (Al and AgAl) result in comparable α spectra, as the absorber layer in both solar cells is obtained from the same deposition. Differences between these two α spectra will appear after light soaking, as will be discussed in section 6.2. As it is difficult to make a detailed comparison of the α spectra of the films and the absorber layers by using only figure 5.2 – figure 5.4, the α spectra are again displayed in figure 5.5 for deposition pressures of 1.35 mbar and 2.40 mbar. For both pressure values, it can be seen that the α spectra of the films obtained from DBP / RT and FTPS / RT match very well, except for the low-energy range where DBP is not sensitive

105 104 103 102 ) -1 101 0

(cm 10 α 10-1 10-2 p=1.35 mbar -3 film, DBP / RT 10 film, FTPS / RT 10-4 absorber layer, FTPS / RT

105 104 103 102 1 ) 10 -1 100

(cm -1 α 10 10-2 -3 p=2.40 mbar 10 film, DBP / RT -4 10 film, FTPS / RT 10-5 absorber layer, FTPS / RT

0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 energy (eV)

Figure 5.5: Absorption coefficient spectra obtained from DBP / RT and FTPS / RT on silicon films deposited at R = 20 and pressures of 1.35 mbar and 2.40 mbar and the absorption coefficient spectra obtained from FTPS / RT on the corresponding solar cells.

enough to measure correctly. Because of the good match between the α spectra obtained from DBP / RT and FTPS / RT on films, the α spectra obtained from DBP / RT on the films that will be discussed in sections 5.3 – 5.5 will not be further discussed in those sections, as they are virtually equal to the α spectra obtained from FTPS / RT on the same films. For a deposition pressure of 2.40 mbar (or any other pressure of at least 2.00 mbar), it can be seen that the α values of the absorber layer are somewhat lower than the α values of the film in the mid-energy range and orders of magnitude lower in the low-energy range. This difference can be partially understood by considering the layers through which the light passes before it reaches the layer of interest in an FTPS measurement. For films, the light first has to pass through the Corning substrate before the film is illuminated, whereas in solar cells, the light passes through the Corning substrate, a TCO layer, a p-layer, and a buffer layer before it ultimately reaches the absorber layer. This means that the light that

78 actually illuminates the layer of interest in an FTPS measurement can be spectrally different in films and solar cell absorber layers. To verify this assumption, the transmittance of a Corning layer, an Asahi (Corning / TCO) layer, an Asahi / p structure, and an Asahi / p / buffer structure have been measured using a Perkin Elmer Lambda 900 spectrophotometer (located at Delft ChemTech) to quantify the supposed absorption in the layer(s) in front of the layer under investigation. For the deposition of the p-layer and the buffer layer, the deposition conditions that are normally used for the deposition of these layers in a solar cell have been used again (see table 5.1). The resulting transmittance curves are depicted in figure 5.6.

1.0

0.8

0.6

0.4

Corning transmittance (-) 0.2 Asahi Asahi / p Asahi / p / buffer 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 energy (eV)

Figure 5.6: Transmittance curves of the structures through which the light passes before the layer of interest in an FTPS measurement is illuminated. In a film, this substrate is just Corning, whereas in a solar cell, the light has to pass through an Asahi / p / buffer structure before the light reaches the i-layer.

It is clear that the transmittance of Corning is high and energy- independent for a very wide range of photon energies. This means that for an FTPS measurement on a film, no correction of the photocurrent spectrum is required, since the transmittance is constant for all energies up to 1.82 eV, which is the typical energy where the photocurrent spectrum is scaled to the absolute α spectrum (see section 4.5.2). For an FTPS measurement on a solar cell, however, the obtained photocurrent spectrum of the absorber layer should be corrected for the energy- dependent transmittance of the Asahi / p / buffer structure. It is this energy-dependent transmittance that explains why the α spectrum of an absorber layer extends to lower α values than the α spectrum of an individual film for the low photon energies, i.e. below ~0.8 eV. For higher photon energies, it does not explain the difference between the two α spectra, since the transmittance of the Asahi / p / buffer structure is approximately energy-independent between 0.8 eV and 1.82 eV (which is the remainder of the spectrum that is measured by FTPS). It is not

79 relevant that the overall transmittance of the Asahi / p / buffer structure is lower than the transmittance of the Corning substrate in this energy range, because a photocurrent spectrum obtained from an FTPS measurement is relative and should thus always be scaled to an absolute α spectrum obtained from an RT measurement (see section 4.5.2). Further, in figure 5.5, it is clear that the uncertainty in the α values for the low-energy range is lower for the absorber layers than it is for the films. This can be explained by the distance over which the photo- generated electrons and holes have to travel before they are collected. Since all absorber layers that are considered in this work are approximately 300 nm thick, this is the maximum distance over which the charge carriers can travel in an absorber layer, whereas in a film this maximum distance is 0.5 mm (the distance between the electrodes; see figure 5.1a). Since the distance over which the charge carriers have to be collected is three orders of magnitude larger in a film than it is in an absorber layer, the recombination losses in a film can be significantly larger than they are in an absorber layer. Additionally, the charge carrier transport in a film predominantly takes place in that part of the film which is closest to the surface, which causes the charge carriers to be more prone to surface recombination than they are in solar cell absorber layers. For this reason, it is plausible to assume that charge carriers created by low-energy photons are collected at a higher rate in a solar cell than they are in a film, resulting in a smoother α spectrum for an absorber layer. Moreover, when performing an FTPS measurement on a solar cell, much fewer scans are required in comparison to an FTPS measurement on a film, which supports the idea that the photo-generated charge carriers suffer less from recombination in an absorber layer than in a film. Typically, a full FTPS measurement on a solar cell (i.e. using all five filters in the FTIR spectrometer) takes only 15 minutes, which is considerably less than the typical measurement time of 40 minutes required for a full FTPS measurement on a film. Note that the electric field in a film and the electric field in an absorber layer are of the same order of magnitude (106 V/m – 107 V/m), so the small difference in electric field between films and absorber layers cannot be said to be the main reason for the lower uncertainty in the α values for films in comparison to absorber layers. Now the α spectra for all films and absorber layers deposited at different pressures have been obtained, several parameters that contain information about the quality of the films and absorber layers can be deduced. Firstly, the α1.2 eV values for both the films and the absorber layers can be determined, so the defect density can be estimated for each sample (see section 3.3.2). The resulting plots of α1.2 eV versus pressure and Nd versus pressure are illustrated in figure 5.7. The films deposited at pressures below 2.00 mbar have a significantly increased α1.2 eV, but do not necessarily have a high defect density. Because these films are not fully amorphous, their defect densities cannot be estimated from α1.2 eV (see figure 5.5a). For the other samples, the defect density can be 16 -2 correlated to α1.2 eV using a proportionality factor of 5×10 cm , as has been discussed in section 3.3.2. The films deposited at pressures above

2.00 mbar are amorphous, and α1.2 eV decreases slightly for increasing pressure. The factor correlating the defect densities of a protocrystalline thin film and the corresponding solar cell absorber layer increases from 1.5 to 4.5 for decreasing deposition pressure. The strong substrate-

102 films, DBP / RT films, FTPS / RT 1018 101 absorber layers, FTPS / RT )

-1 17

10 )

0 -3

(cm 10 eV (cm d 1.2 1.2 α 1016 N 10-1

1015 10-2 1.41.61.82.02.22.42.6 pressure (mbar)

Figure 5.7: α1.2 eV and Nd as a function of deposition pressure of films and corresponding solar cell absorber layers deposited at R = 20 obtained from FTPS / RT and DBP / RT. The values obtained from DBP / RT and FTPS / RT on the films match very well which confirms the accuracy of FTPS. Note that the α1.2 eV values of the films deposited at pressures below 2.00 mbar do not directly correspond to Nd values via the proportionality factor of 5×1016 cm-2, as these films are not fully amorphous.

dependence in the protocrystalline growth regime (see section 3.3.2) can explain the difference in α1.2 eV between the solar cells with amorphous absorber layers and the corresponding films. Further, the Defect-Pool Model (see section 3.3.1) states that the defect density of the absorber layer in a solar cell is dependent on the Fermi level. The Fermi level varies throughout the absorber layer, whereas the Fermi level in a film is constant. The resulting difference in defect distribution in the absorber layer of a solar cell and a film could explain the observed difference in defect density. Note that the difference in α1.2 eV between the amorphous films and solar cell absorber layers cannot be attributed to the decreasing transmittance of the front part of the solar cell (Asahi / p / buffer) in the (near) infrared part of the spectrum (see figure 5.6), because 1.2 eV is still in the energy-independent part of the transmittance of the Asahi / p / buffer structure. A possible difference in collection between films and solar cells cannot explain the difference in α1.2 eV either, since recombination is a wavelength-independent process. As discussed in section 3.3.2, the defect density can also be estimated from the α spectrum by integrating over the photon energies corresponding to defect states. To compare the difference between the

α1.2 eV estimation and the integration method, both methods have been used to estimate Nd. The result of these calculations for both the films and the absorber layers deposited at different pressures are displayed in figure 5.8. It is directly clear from the figure that both methods used for estimating Nd result in the same trend: higher deposition pressures result in lower defect densities. This conclusion holds for both the films and the

1017 films absorber layers α estimation α estimation 1.2 eV 1.2 eV integration integration R=0 reference R=0 reference

) 16 -3 10 (cm d N

1015

1.4 1.6 1.8 2.0 2.2 2.4 2.6 pressure (mbar)

Figure 5.8: Defect density as a function of deposition pressure of films and corresponding solar cell absorber layers obtained from the α spectrum using the α1.2 eV estimation and the integration method. Since the films deposited at pressures below 2.00 mbar are not fully amorphous, these films are not further considered in the comparison of the two methods used for estimating the defect density.

absorber layers, even though for every investigated pressure value, the Nd values of the absorber layers are lower than the Nd values of the films. The reason for this difference in Nd between films and the corresponding absorber layers has been discussed earlier in this subsection: the α values in the low- and mid-energy range are lower for an absorber layer than they are for the corresponding film. Further, it can be seen that the α1.2 eV estimation results in Nd values that are 2 – 4 times larger than the Nd values obtained from the integration method. This difference could be minimised by appropriately adjusting the proportionality factors used in both methods, since there is no consensus on the exact values of these constants [83]. Therefore, the Nd values displayed in figure 5.8 and in the remainder of this work should not be considered as completely accurate, but merely as useful indicators of the order of magnitude of Nd and the quality of the material. Following this reasoning, both methods that have been used to estimate Nd give useful results, but because the integration method has a better physical foundation than the α1.2 eV estimation, the latter method will not be further considered in estimations of Nd in the remainder of this work. Finally, it can be said that for the films and absorber layers deposited at pressures of at least 2.00 mbar, it holds that 16 -3 Nd < 10 cm , which corresponds to device-quality material. For the R = 0 reference film and absorber layer, there is no significant difference 16 -3 16 -3 between their Nd values (1.1×10 cm versus 1.5×10 cm ), which will be further discussed in the remainder of this subsection. Note that the Nd values of the R = 0 film and absorber layer have been estimated only by means of the integration method, as it has been chosen to no longer use the α1.2 eV estimation.

Apart from Nd, several other parameters that contain information about the material and its quality, such as E04, ET, EK, and EU (see sections 3.3.2 and 3.3.3), can be deduced from the α spectrum. These four parameters are depicted in figure 5.9 as a function of the deposition pressure. Firstly, in the top graph, it can be seen that for the films and the absorber layers, all E04 values are exactly equal. This is due to the fact that all E04 values are determined from that part of the α spectrum that has been determined by means of RT. Remember now that for the scaling of each photocurrent spectrum obtained from FTPS on a film and on the corresponding absorber layer, the RT measurement of the film has been used in both cases, since no RT measurement on the absorber layer can be performed. Further, for all but the lowest pressure, the E04 values are 1.94 eV – 1.96 eV, which roughly indicates that these samples should be amorphous. For the films deposited at pressures below 2.00 mbar, this is, however, not the case, which illustrates that E04 is not a very accurate

2.05 films absorber layers R=20 series R=20 series 2.00 R=0 reference R=0 reference

(eV) 1.95 04 E 1.90

1.80 1.60 1.40 (eV) T 1.20 E 1.00

1.80 1.60 1.40 (eV)

K 1.20 E 1.00

70 60 50

(meV) 40 U E 30 1.4 1.6 1.8 2.0 2.2 2.4 2.6 pressure (mbar)

Figure 5.9: E04, ET, EK, and EU as a function of deposition pressure of films and corresponding solar cell absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and absorber layers deposited at R = 20, E04, ET, EK, and EU of a reference film and absorber layer deposited at R = 0 are included in each of the four graphs.

83 parameter to determine the phase of the material. Only for the film deposited at 1.35 mbar, E04 is significantly higher than it is for the other deposition pressures, indicating a crystalline fraction in the material. As said at the beginning of this section, this has already been confirmed by Raman measurements, which give much clearer results about the crystallinity of each of the films than E04. Finally, note that E04 of the absorber layer deposited at 1.35 mbar is probably too high and is more likely to be ~1.95 eV, as the sub-band gap α spectrum of this absorber layer does not show any similarity to a typical sub-band gap α spectrum of a (micro)crystalline material (see figure 5.2 and figure 3.6). The reference film deposited at R = 0 shows an E04 of 1.90 eV, indicating that this film is amorphous. The E04 values of the R = 0 samples are lower than the E04 values of the R = 20 samples, which will later be seen to result in a lower

Voc for the reference solar cell with an R = 0 absorber layer, when compared to the solar cell with the R = 20 absorber layers.

From the ET plot in figure 5.9, the phase transition in the film series can clearly be seen: for pressures below 2.00 mbar, there is a strong decrease in ET from ~1.79 eV to ~1.11 eV. Since the phase transition does not occur in the absorber layers, ET does not show a similar decrease for the absorber layers. For the pressures resulting in amorphous films and absorber layers, there is a slightly increasing trend in ET for increasing pressure, and for all these pressures ET < 1.8 eV, corresponding to device-quality material. The same reasoning holds for the EK values: the phase transition in the film series for pressures below 2.00 mbar is illustrated by the strong decrease in EK for decreasing pressure, and for pressures of 2.00 mbar and higher, the EK values correspond to device- quality values (EK < 1.6 eV) with a slightly increasing trend in the EK plots for increasing pressure. Note that for pressures of 2.00 mbar and higher, both ET and EK of the undiluted reference material are close to the values of the R = 20 samples and smaller than 1.8 eV and 1.6 eV respectively, which means that the ET and EK values of the R = 0 reference film and absorber layer also correspond to device-quality values.

For a-Si:H material to be considered device-quality, EU should be 50 meV or less (see section 3.3.2). From figure 5.9, it is clear that this is the case for the R = 0 reference samples and all R = 20 samples, except for the films deposited at pressures below 2.00 mbar. Since these films consist for a significant part of (a+ μc)-Si:H and μc-Si:H in addition to the a-Si:H bottom layer, EU is no longer smaller than 50 meV, which means that these films are not device-quality. This holds in particular for the film deposited at 1.79 mbar, which consists mainly of (a+ μc)-Si:H, considering the earlier mentioned Raman measurements and its α spectrum (see figure 5.2 or figure 5.3). Since for this α spectrum there is almost no energy range for which the spectrum shows the exponential trend that is required for determining EU, it is difficult to estimate EU and its value is possibly even higher than the value displayed in figure 5.9.

Further, a striking difference in EU can be seen between the R = 20 films and the R = 20 absorber layers for pressures of 2.00 mbar and higher: while the films show reasonable device-quality EU values (43.4 meV – 47.8 meV), the absorber layers all seem to have very low EU values (29.4 meV – 32.0 meV). Because this large difference in EU between films and absorber layers does not appear for the R = 0 samples, the impression arises that the hydrogen dilution greatly influences the

84 quality of the grown material, i.e. that the quality of the R = 20 absorber layers is much higher than the quality of the R = 0 absorber layer.

However, this hypothesis cannot be confirmed when the Nd values of the R =20 absorber layers and the R = 0 absorber layers are compared, nor when considering their FF or η (see section 3.5.3 and figure 5.10). Because the quality of the R = 0 absorber layer is likely to be higher than the quality of the R = 20 absorber layers (the R = 0 absorber layer has a lower Nd and a higher FF and η than the R = 20 absorber layers), the EU values of the R = 20 absorber layers cannot be expected to be much lower than the EU values of the R = 0 absorber layer. Moreover, the FTPS measurement time of the two types of absorber layers is virtually equal, which implies that there is no large quality difference between the two materials. For now, the low EU values of the R = 20 absorber layers are accepted in the sense that they correspond to device-quality values and

0.88 0.86 0.84 (V)

oc 0.82 V 0.80

16.0

) 15.0 2 14.0 13.0 (mA/cm sc

J 12.0

0.72 0.70 0.68

FF (-) 0.66 0.64

10.0 R=20 absorber layers Al 9.0 AgAl 8.0 (%)

η 7.0 R=0 reference Al 6.0 AgAl 1.4 1.6 1.8 2.0 2.2 2.4 2.6 pressure (mbar)

Figure 5.10: The external parameters Voc, Jsc, FF, and η as a function of deposition pressure of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs. Note that the solar cell with the R = 0 absorber layer and the solar cell with the R = 20 absorber layer deposited at 2.00 mbar have been deposited with both an Al and an AgAl back contact.

85 that there is no clear trend within the investigated pressure range, but the exact values should be interpreted with a certain scepticism. Finally, JV measurements have been performed on the solar cells with the R = 0 and R = 20 absorber layers. The resulting plots of Voc, Jsc, FF, and η as a function of the deposition pressure are depicted in figure 5.10. Firstly, it can be seen that for a deposition pressure of 1.35 mbar, the values for all external parameters are significantly lower than they are for the higher pressures. This has to be caused by an energy-independent loss process, because the values of Nd, ET, EK, and EU (indirectly obtained from FTPS) for this absorber layer do not indicate that this absorber layer is of low quality. Therefore, it is likely that there are recombination losses somewhere in the path of the photocurrent in this solar cell, for instance caused by a barrier at the p-i interface. For all pressures above 1.35 mbar, an increasing solar cell performance can be seen for increasing pressure, which is in line with the earlier discussed decreasing trend in Nd for increasing pressure (see figure 5.8). Further, the Voc for the R = 0 reference solar cell is notably lower than the Voc of the solar cells with the R = 20 absorber layers. This is line with the aforementioned difference in E04 between the R = 0 and the R = 20 absorber layers. When considering Jsc, FF, and η, it can be seen that the values for the solar cells with the R = 20 absorber layers are notably lower than they are for the reference solar cell with the R = 0 absorber layer, which is a known result from earlier work [118]. This difference will become smaller after light soaking, as will be demonstrated in section 6.2. From figure 5.10, it is also possible to make a comparison between the two back contact configurations (Al and AgAl). For the two solar cells with the absorber layers deposited at R = 20, the absorber layer is exactly the same, as it has been obtained from one deposition. Therefore, the only difference between the solar cell with the AgAl back contact and the solar cell with the Al contact that is expected, is a higher Jsc for the solar cell with the AgAl back contact, because AgAl has a higher reflectance than Al [121]. However, it is clear from figure 5.10 that also the FF is lower for the solar cell with the AgAl back contact. Since there is no difference between the i-layers in the solar cells that have been deposited with the different back contacts, the difference in FF is best explained as a measurement irregularity. Because the differences between the solar cells with the two different back contact configurations have now been discussed, there is no need to further discuss the solar cells with the AgAl back contacts in sections 5.3 – 5.5, but their behaviour during light soaking will still be discussed in section 6.2. Concluding, it can be said that within the R = 20 pressure series the solar cells with the highest η and FF contain absorber layers deposited at pressures between 2.20 mbar and 2.60 mbar: the highest η is 7.9% and the highest FF is 0.71. The η value for the reference solar cell with the undiluted absorber layer is significantly higher: 8.7%. As stated earlier, this difference in solar cell performance will be strongly reduced after light soaking, as will be discussed in section 6.2.

5.3 Variation of the rf-power To investigate the influence of the rf-power on the properties of the absorber layer, a systematic study is performed of the effect of the rf- power on the quality of the deposited material. For this reason, both films and absorber layers have been deposited with rf-powers varying between 4 W and 16 W, while keeping the other deposition conditions constant (see section 5.1). The absorption coefficient spectra obtained from FTPS and RT measurements on the Si:H films and the corresponding solar cell absorber layers deposited at different rf-powers are depicted in figure 5.11. Contrary to the α spectra of the pressure series that were discussed in the previous section, there is no indication that any of the films or absorber layers deposited at different rf-powers results in mixed-phase or microcrystalline material. Further, it is already clear from this figure that the EU values and the low-energy α values are significantly lower for the absorber layers than they are for the films, but as this has already been discussed in section 5.2, it will not be discussed again here. Since the α spectra are so similar for both the films and the absorber layers, it is hard to identify whether there are quality differences between the series of films and absorber layers. Therefore, it is worth considering

Nd for both series of samples. The result of integrating all the α spectra over the photon energies corresponding to the defect states is presented in figure 5.12. For comparative purposes, the Nd values of an R = 0 reference film and absorber layer have been included. Note that these R = 0 samples are identical to the R = 0 samples discussed in section 5.2. Further, the R = 20 samples deposited at 4 W are equal to the R = 20 samples deposited at 2.00 mbar that were discussed in section 5.2.

As is clear from figure 5.12, the Nd values of all films and absorber layers deposited at different rf-powers correspond to device-quality 16 -3 values, since Nd < 10 cm for all samples. For the films, a constant trend in Nd can be seen for all rf-powers, with the exception of the film deposited at 16 W, which has a slightly lower Nd value. For the absorber layers, it seems that Nd increases slightly for increasing rf-power. Just as was considered for the pressure series in section 5.2, several physical explanations for this difference can be given (substrate-dependent growth or different defect distributions). In this section, the differences between the α spectra of the films and absorber layers will not be discussed again. It will only be attempted to find the optimal rf-power. This is, however, not easily done by using only figure 5.12, since the Nd values of the absorber layers vary by a relatively small amount (less than a factor of 2). Therefore, it is better to first consider other material parameters, such as

E04, ET, EK, EU, and the external parameters of the solar cells, before making a definite statement on this supposed trend in the quality of the absorber layers. Plots of E04, ET, EK, and EU as a function of the rf-power are depicted in figure 5.13. Just as for the pressure series, it can be seen in the top graph that for the films and the absorber layers, all E04 values are exactly equal, because the values have been calculated from the same RT measurement data. It seems that E04 increases for rf-powers of 10.3 W and above from 1.96 eV to 1.99 eV, possibly indicating an increased hydrogen concentration in this film. Attributing the increased E04 value to a certain crystalline fraction in the material would be too far-reaching, since this is

105 104 103 102

) 1 -1 10 100 (cm

α films 10-1 4.0 W -2 10 7.2 W 10-3 10.3 W -4 13.5 W 10 16.0 W

105 104 103 102 101 ) 0 -1 10 10-1 (cm -2 α 10 absorber layers 10-3 4.0 W 7.2 W 10-4 -5 10.3 W 10 13.5 W -6 10 16.0 W

0.60.81.01.21.41.61.82.02.22.4 energy (eV)

Figure 5.11: Absorption coefficient spectra obtained from FTPS / RT on silicon films and corresponding solar cell absorber layers deposited at R = 20 and varying rf-powers.

films absorber layers R=20 series R=20 series 1016 R=0 reference R=0 reference ) -3 (cm d N

1015

4 6 8 10121416 power (W)

Figure 5.12: Defect density as a function of rf-power of films and corresponding solar cell absorber layers obtained from their α spectra.

2.05 films absorber layers R=20 series R=20 series 2.00 R=0 reference R=0 reference

(eV) 1.95 04 E 1.90

1.85

1.80

(eV) 1.75 T E 1.70

1.70

1.65

(eV) 1.60 K E 1.55

40 (meV) U E 30

4 6 8 10121416 power (W)

Figure 5.13: E04, ET, EK, and EU as a function of rf-power of films and corresponding solar cell absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and absorber layers deposited at R = 20, E04, ET, EK, and EU of a reference film and an absorber layer deposited at R = 0 are included in each of the four graphs.

not confirmed by the α spectra in figure 5.11, or by earlier performed Raman measurements. It has, however, become clear that the microstructure factor, which indicates the porosity of a material, increases for rf-powers of 10.3 W and higher [118]. This means that the quality of the deposited films decreases for these high rf-powers. ET and EK show constant device-quality values of ~1.8 eV and ~1.65 eV for the lower end of the investigated rf-power range, and a slightly decreasing trend can be seen for increasing rf-power. When EU is now considered, a clearly increasing trend for increasing rf-power can be seen for both the films and the absorber layers. The increase in EU for the absorber layers is in line with the increase in Nd that was discussed earlier in this section, but the increase in EU for the films does not correspond to a similar increase in Nd. However, it could be that there is an increased disorder in the films without the introduction of more defects. Moreover, there is a substantial error on all EU values and even more on the Nd values, so the different

0.86

0.84

(V) 0.82 oc

V R=20 absorber layers 0.80 R=0 reference

15.0 ) 2 14.0

13.0 (mA/cm

sc 12.0 J

0.72

0.68

0.64 FF (-) 0.60

9.0

8.0

(%) 7.0 η 6.0

4 6 8 10121416 power (W)

Figure 5.14: The external parameters Voc, Jsc, FF, and η as a function of rf- power of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs.

trends in EU and Nd for the films should not directly be interpreted as contradictory. Further, all films and absorber layers show device-quality EU values of less than 50 meV. Note that the difference in the EU values between the films and the absorber layers has already been discussed in section 5.2, so it will not be discussed again here. Finally, the external parameters of the solar cells with the absorber layers deposited at different rf-powers have been obtained by performing JV measurements. The resulting plots of the external parameters versus the rf-power are depicted in figure 5.14. The decreasing trend in Voc for increasing rf-power is in line with the earlier mentioned decrease in ET and EK for increasing rf-power. The Voc value of the solar cell with an absorber layer deposited at 13.5 W seems to be abnormally low, but this can be considered an experimental irregularity (insufficient annealing before performing the JV measurement), since it is not further reflected in the other external parameter plots. The decreasing trend in FF for increasing rf-power is in line with the trends in EU and Nd of the absorber layers,

90 which have been discussed earlier in this section. Now it can safely be stated that absorber layers deposited at rf-powers of 10.3 W and higher are indeed of lower quality than the absorber layers deposited at lower rf- powers. In general, when considering the η plot, it can be said that absorber layers deposited at lower rf-powers correspond to the solar cells with the highest performance. Since 4 W is the lowest value in the investigated rf-power range, using this rf-power for the deposition of the absorber layer results in the highest performance solar cell within this series.

5.4 Variation of the silane flow To investigate the influence of the silane flow on the properties of the absorber layer, a systematic study is performed of the effect of the silane flow on the quality of the deposited material. For this reason, both films and absorber layers have been deposited with silane flows varying between 1 sccm and 10 sccm, while keeping the other deposition conditions constant (see section 5.1). Note that the value of 10 sccm is the maximum flow value that can be achieved with the particular PECVD system that has been used for the deposition of a layer with a hydrogen- to-silane dilution ratio of 20. The limiting factor is not the silane flow as such, but the hydrogen flow, which has to be set to the maximum value of 200 sccm to maintain the R = 20 condition. Further, the film and absorber layer deposited using a silane flow of 5 sccm are equal to the films and absorber layers deposited at 2.00 mbar and 4 W that were discussed in section 5.2 and 5.3 respectively. The absorption coefficient spectra obtained from FTPS and RT measurements on the Si:H films and the corresponding solar cell absorber layers deposited at different silane flows are depicted in figure 5.15. Similar to the films and absorber layers deposited at different rf- powers that were discussed in section 5.3, the films and absorber layers deposited at different silane flows all appear to be amorphous, when considering their α spectra. Making further statements about the quality of individual films and absorber layers within these flow series is too difficult when only the α spectra are considered. Therefore, the Nd values for both series of samples are considered again. The resulting plots of Nd versus the silane flow obtained from integration of the α spectra (see section

3.3.2) are depicted in figure 5.16. As opposed to the Nd plots in the pressure and power series discussed in the previous sections (see figure 5.8 and figure 5.12), a more or less constant trend can be seen for both the films and absorber layers deposited using different silane flows. This would mean that the silane flow does not greatly affect the quality of the deposited material, or at least not in the investigated silane flow range. To verify this hypothesis, the films and absorber layers are further analysed by considering their E04, ET, EK, and EU values that are deduced from the α spectra depicted in figure 5.15. These four parameters are depicted in figure 5.17 as a function of the silane flow. For the film deposited at the highest silane flow of 10 sccm, an increased E04 can be seen in the graph. Even though it is clear from the α spectra that there are only amorphous films and absorber layers within these series, it is possible that the film deposited using a silane flow of 10 sccm has a

105 104 103 102

) 1 -1 10 100 (cm

α -1 films 10 1.0 sccm 10-2 3.0 sccm -3 5.0 sccm 10 7.5 sccm 10-4 10.0 sccm

105 104 103 102 101 ) 0 -1 10 10-1 (cm -2 α 10 absorber layers 1.0 sccm 10-3 3.0 sccm -4 10 5.0 sccm 10-5 7.5 sccm 10-6 10.0 sccm

0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 energy (eV)

Figure 5.15: Absorption coefficient spectra obtained from FTPS / RT on silicon films and corresponding solar cell absorber layers deposited at R = 20 and varying silane flows.

slightly increased hydrogen concentration in the continuous random network of the amorphous material. For the other films and absorber layers, there is a roughly constant trend in the E04, ET, and EK plots and all ET and EK values correspond to device-quality values. When considering the EU values of the films and the absorber layers deposited using different silane flows, it seems that there is an increasing trend in EU for the films with increasing silane flow and that EU is constant for the absorber layers. As there is only a minor indication from the Nd values that the films deposited at higher silane flows are indeed of lower quality than the films deposited at lower silane flow values, it is unlikely that there is in fact a significant quality difference within this series of films.

When closely inspecting the EU plot of the films, it can be seen that the increasing trend is predominantly caused by the high EU value of the film deposited using a silane flow of 10 sccm, which is probably due to some deposition problem for this particular film. This is further supported by the increased E04 value for this film. Apart from this sample, EU is roughly

films absorber layers 1016 R=20 series R=20 series R=0 reference R=0 reference ) -3 (cm d N

1015

12345678910 SiH flow (sccm) 4

Figure 5.16: Defect density as a function of silane flow of films and corresponding solar cell absorber layers obtained from their α spectra.

2.05 films absorber layers R=20 series R=20 series 2.00 R=0 reference R=0 reference

(eV) 1.95 04 E 1.90

1.85

1.80

(eV) 1.75 T E 1.70

1.70

1.65

1.60 (eV) K E 1.55

40 (meV) U

E 30

12345678910 SiH flow (sccm) 4

Figure 5.17: E04, ET, EK, and EU as a function of silane flow of films and corresponding solar cell absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and absorber layers deposited at R = 20, E04, ET, EK, and EU of a reference film and an absorber layer deposited at R = 0 are included in each of the four graphs.

0.86

0.84

(V) 0.82 oc

V R=20 absorber layers 0.80 R=0 reference

15.0 ) 2 14.0

13.0 (mA/cm

sc 12.0 J

0.72

0.68

0.64 FF (-) 0.60

9.0

8.0

(%) 7.0 η 6.0

12345678910 SiH flow (sccm) 4

Figure 5.18: The external parameters Voc, Jsc, FF, and η as a function of silane flow of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs.

constant and does not clearly depend on the silane flow, so the silane flow does not have a significant influence on the quality of the deposited films and absorber layers. Further, all EU values are below 50 meV, so all samples show device-quality EU values. The idea that the silane flow does not affect the quality of the absorber layers is further confirmed when the external parameters of the solar cells with the absorber layers deposited using different silane flows are considered. The plots of the external parameters as a function of the silane flow, as obtained from JV measurements, are depicted in figure 5.18. None of the external parameters show a significant dependence on the silane flow used for the deposition of the absorber layer and all solar cells show consistently high FF and η values. When the exact numerical values of FF and η are considered, the solar cell with the absorber layer deposited using a silane flow of 5 sccm is the best within this series, but the differences with the other solar cells are so small (less than 0.5%

94 variation on the η) that it is better to conclude that all investigated silane flows result in an equally high quality of the absorber layer material.

5.5 Variation of the deposition temperature The last deposition parameter that is considered in the optimisation procedure described in section 5.1 is the substrate temperature. To investigate the influence of this deposition parameter on the properties of the absorber layer, a systematic study is performed of the effect of the substrate temperature on the quality of the deposited material. For this reason, both films and absorber layers have been deposited with substrate temperatures varying between 150 °C and 200 °C, while keeping the other deposition conditions constant. Further, the film and absorber layer deposited using a substrate temperature of 180 °C are equal to the films and absorber layers deposited at 2.00 mbar, 4 W, and 5 sccm that were discussed in section 5.2, 5.3, and 5.4 respectively. The absorption coefficient spectra obtained from FTPS and RT measurements on the Si:H films and the corresponding solar cell absorber layers deposited at different substrate temperatures are depicted in figure 5.19. From the shape of the absorption coefficient spectra of the absorber layers, there is a clear indication that all absorber layers are amorphous. This is not the case for the films, since some absorption coefficient spectra indicate the presence of mixed-phase material in the film. A more detailed analysis is required to investigate the differences within the series of films and absorber layers to be able to make a definite statement on the quality of each of the deposited materials. For this reason, the Nd values for both the series of films and absorber layers are considered. The resulting plots of Nd versus the substrate temperature are obtained from integration of the α spectra (see section 3.3.2) and are depicted in figure 5.20. Concerning the films, there are three substrate temperatures in the ° investigated range that result in a significantly increased Nd value (160 C, 190 °C, and 200 °C) which can be an indication of a crystalline fraction in the material. After analysing the results from Raman measurements on these films, it has been shown that only the film deposited at 200 °C has a certain crystalline fraction. The films deposited at 160 °C and 190 °C do not show a crystalline fraction from Raman measurements [118]. Overall, it can be said that within the series of films, Nd increases for increasing substrate temperature. An even clearer trend can be seen for the absorber layers, for which Nd increases monotonically for increasing substrate temperature. Further, there is no indication that one of the absorber layers is not fully amorphous. Summarising, it can be stated that from the Nd trends in both series of samples, there is a good indication that the material with the highest quality is deposited at low substrate temperatures. To further confirm this theory, the values of E04, ET, EK, and EU are investigated. The plots of these four material parameters as a function of the substrate temperature are depicted in figure 5.21.

From the E04 plot, it cannot be seen that not all films are fully amorphous, which again proves that E04 should only be regarded as a rough indicator of the crystallinity or structural order of a material. The amorphous films that show a high Nd value also show an increased ET value in comparison to the other amorphous films (~1.84 eV versus

105 104 103 102

) 1 -1 10 films o 100 150 C (cm o α 10-1 160 C o -2 170 C 10 o 180 C -3 10 190 oC o 10-4 200 C

105 104 103 102 101 ) 0 -1 10 absorber layers -1 10 o

(cm 150 C -2 α 10 160 oC -3 10 170 oC 10-4 180 oC 10-5 190 oC o 10-6 200 C

0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 energy (eV)

Figure 5.19: Absorption coefficient spectra obtained from FTPS / RT on silicon films and corresponding solar cell absorber layers deposited at R = 20 and varying substrate temperatures.

~1.80 eV), which confirms the lower material quality of these films. ° Further, it is clear that the film deposited at 200 C shows the lowest ET and EK values of all films within this series, which is due to its significant crystalline phase. When the EU plot is considered, the EU values of the films deposited at 160 °C, 190 °C, and 200 °C are significantly higher than the EU values of the other films, which is in line with their increased Nd values. For the other films, it can be said that they show device-quality values, since EU < 50 meV. For the absorber layers, the trend is also comparable to the trend in the Nd plot: EU increases slightly for increasing substrate temperature. In general, it can thus be stated that EU increases for increasing substrate temperature, meaning that the material with the highest quality is deposited at the lower substrate temperatures, which was already suspected from the Nd values. To further confirm this trend, JV measurements have been performed on the solar cells with absorber layers deposited at different substrate temperatures. The resulting plots of the external parameters as

films absorber layers 1017 R=20 series R=20 series R=0 reference R=0 reference ) -3

(cm 10 d N

1015

150 160 170 180 190 200 temperature (oC)

Figure 5.20: Defect density as a function of substrate temperature of films and corresponding absorber layers obtained from their α spectra.

2.10 films absorber layers 2.05 R=20 series R=20 series R=0 reference R=0 reference 2.00 (eV)

04 1.95 E 1.90

1.85

1.80

(eV) 1.75 T E 1.70

1.70

1.65

1.60 (eV) K E 1.55

70 60 50

(meV) 40 U E 30 150 160 170 180 190 200 temperature (oC)

Figure 5.21: E04, ET, EK, and EU as a function of substrate temperature of films and corresponding absorber layers deposited at R = 20 obtained from their α spectra. As a reference, for both series of films and absorber layers deposited at R = 20, E04, ET, EK, and EU of a reference film and an absorber layer deposited at R = 0 are included in each of the four graphs.

0.92 R=20 absorber layers R=0 reference 0.89

(V) 0.86 oc V 0.83

15.0 ) 2 14.0

13.0 (mA/cm

sc 12.0 J

0.72

0.70

0.68 FF (-) 0.66

9.0

8.0

(%) 7.0 η 6.0

150 160 170 180 190 200 temperature (oC)

Figure 5.22: The external parameters Voc, Jsc, FF, and η as a function of substrate temperature of the solar cells with absorber layers deposited at R = 20. As a reference, the external parameters of a solar cell with an absorber layer deposited at R = 0 are included in each of the four graphs.

a function of the substrate temperature are depicted in figure 5.22. There is a clear decreasing trend in Voc for increasing substrate temperature, which is in line with the decreasing trend in EK for increasing substrate temperature. Further, the decreasing trend in FF is in line with the increasing trend in Nd and EU for increasing substrate temperature. Concluding, it can thus be said that the lowest substrate temperature in the investigated range, which is 150 °C, results in the highest material quality, as the solar cell with the absorber layer deposited at this substrate temperature results in the highest FF and η values.

6 Photo-induced degradation of a-Si:H films and solar cells In this chapter, the optimisation procedure discussed in the previous chapter will be expanded to an optimisation of the deposition conditions after light soaking or photo-induced degradation (see section 3.4) of all samples. To investigate the effect of light soaking in all samples, an experimental setup has been used to illuminate the samples, which is briefly discussed in section 6.1. In sections 6.2 to 6.5, the effect of light soaking on the different series of films and solar cell absorber layers deposited at different deposition conditions (see section 5.1.2) is discussed. These sections should be regarded as continuations of sections

5.2 – 5.5 respectively. The degradation of the Jsc after stabilisation of the FF is further investigated in section 6.6. Finally, in section 6.7, the results of an outdoor light soaking experiment are discussed.

6.1 Experimental details The films and solar cells are light-soaked in a custom-designed degradation setup using metal halide lamps at a power density of 100 mW/cm2. All samples are kept at a constant temperature of 50 °C. The films and solar cells are illuminated through the glass substrate under open-circuit conditions. The absorption coefficient spectra of both the silicon films and the corresponding solar cell absorber layers are obtained by means of FTPS / RT in the initial state, after 1.3 hours of light soaking, and after 173 hours of light soaking. The RT measurement on the film is only performed in the initial state, as no changes in the absorption coefficient spectrum are expected for the super-band gap photon energies, which is the energy range where the RT measurement data are used to calculate the absorption coefficient spectrum. The external parameters of the solar cells are monitored in time by means of repeated JV measurements performed under standard illumination conditions (see section 3.5.3) using an Oriel Corporation solar simulator. Note that all measurement results of the samples in the initial state have already been discussed in sections 5.2 – 5.5 and are included again in the following sections to monitor the behaviour of the different films and absorber layers during light soaking.

6.2 Degradation of the pressure series After the evaluation of the series of films and corresponding solar cell absorber layers deposited at different pressures while keeping the other deposition conditions constant in section 5.2, the results of the pressure series after light soaking will be evaluated in this section. This evaluation will be done in the same way as the results of the pressure series were discussed in section 5.2. Firstly, the α spectra of the films and the absorber layers are determined after 1.3 hours of light soaking and after 173 hours of light soaking by means of FTPS / RT, and compared to the initial α spectra (i.e. before light soaking). The structural phase of the material does not change upon illumination, so the general shape of the α

105 104 103 102

) 1 -1 10 100 (cm α 10-1 10-2 p=1.35 mbar -3 initial 10 after 1.3 hours 10-4 after 173 hours

105 104 103 102

) 1 -1 10 100 (cm α 10-1 10-2 p=2.60 mbar initial 10-3 after 1.3 hours 10-4 after 173 hours

0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 energy (eV)

Figure 6.1: Absorption coefficient spectra obtained from FTPS on silicon films deposited at R = 20 and pressures of 1.35 mbar and 2.60 mbar at three different moments during the light soaking experiment: initial, after 1.3 hours, and after 173 hours.

spectrum does not change for any film or absorber layer. Therefore, only the α spectra of two R = 20 films deposited at different pressures (1.35 mbar and 2.60 mbar) are depicted in figure 6.1 to illustrate the influence of the SWE (see section 3.4) on the α spectra. In this figure, it can be seen that the α values for photon energies corresponding to the defect states in the middle of the band gap (between the tail states of the conduction band and the valence band) increase upon illumination due to an increase of the number of dangling bonds, while there is no significant change in the α spectra for higher photon energies. This means that it is not interesting to review the values of E04, ET, EK, and EU again after light soaking, since they are all determined from the energy range above the energy range corresponding to the defect states. Because light soaking does not induce changes in the α spectrum for these photon energies, the values of E04, ET, EK, and EU do not change after light soaking. For the predominantly microcrystalline film deposited

100 at 1.35 mbar, an increase in the α values is observed below ~1.0 eV, while for the fully amorphous film deposited at 2.60 mbar, an increase in the α values is observed for all photon energies below ~1.6 eV, as the optical band gap of the fully amorphous film is much higher than the optical band gap of the film deposited at 1.35 mbar (see section 5.2). This means that the increase in integrated absorption – or the increase in Nd – is orders of magnitude larger in the film deposited at the higher pressure. For this reason, it appears that μc-Si:H does not suffer from the SWE, but, as can be seen in the top graph of figure 6.1, there is still a photo-induced degradation for this material. However, the SWE is much less pronounced in μc-Si:H, because the increase in integrated absorption upon illumination is much lower in μc-Si:H than it is in a-Si:H. During light soaking, all α spectra show an increase in the low- energy α values that is similar to the increase illustrated in figure 6.1.

R=20 films initial after 1.3 hours 1016 after 173 hours

R=0 reference )

-3 initial after 1.3 hours (cm

d after 173 hours N

1015

R=20 absorber layers initial: Al initial: AgAl 1016 after 1.3 hours: Al after 1.3 hours: AgAl after 173 hours: Al )

-3 after 173 hours: AgAl (cm

d R=0 reference N initial: Al initial: AgAl after 1.3 hours: Al 1015 after 1.3 hours: AgAl after 173 hours: Al after 173 hours: AgAl 1.41.61.82.02.22.42.6 pressure (mbar)

Figure 6.2: Defect density as a function of deposition pressure of films and corresponding solar cell absorber layers obtained from their α spectra using the integration method at three different moments during the light soaking experiment. Since the films deposited at pressures below 2.00 mbar are not fully amorphous, their Nd values are not further considered and therefore they have been omitted from the graph.

101

Therefore, it is not considered interesting to display all the individual α spectra of the films and absorber layers during the light soaking experiment, just as they were displayed in the initial state in figure 5.2 and figure 5.4. It is more interesting to investigate the increase in Nd of all films and absorber layers during the light soaking experiment. The resulting plots of Nd as a function of the deposition pressure at three different moments during the light soaking experiment are depicted in figure 6.2. For both the amorphous films and the absorber layers, a similar increase in Nd can be seen, meaning that the degradation rate is not dependent on the deposition pressure. As a consequence of the pressure-independent degradation rate, the R = 20 films and absorber layers deposited at the higher pressures are also after 173 hours of light soaking the samples with the lowest Nd values. Further, the relative degradation of the R = 0 reference material is larger than the relative degradation of the R = 20 material, which is in line with the idea that layers deposited from hydrogen-diluted SiH4 suffer less from the SWE than layers deposited from undiluted SiH4 (see section 5.1.1). Further, it can be seen that the relative degradation of the solar cells with the AgAl back contacts is slightly larger than the relative degradation of their counterparts with the Al back contacts. This can be understood by realising that the reflection of Ag is larger than the reflection of Al (see figure 4.5), causing the effective intensity of the light in the absorber layer to be greater for the solar cells that are supplied with an AgAl back contact in comparison to the solar cells with the same absorber layer, but with an Al back contact. To monitor the performance of the solar cells during the light soaking experiment, repeated JV measurements have been performed. By normalising each of the external parameters to their initial values, the plots of the normalised external parameters versus time can be obtained. The resulting four graphs contain information about the relative degradation of the absorber layers and are depicted in figure 6.3. To diminish the uncertainty in the data values depicted in figure 6.3 (and also in figure 6.4), all depicted values of the external parameters are in fact an average of three values. This average can be obtained because for each solar cell, multiple identical back contacts – otherwise known as “dots” – are deposited next to each other on top of the n-layer, which means that multiple specimens are available of every solar cell that is discussed in this thesis.† The three dots that are used for the calculation of the average of each of the external parameters are those dots that correspond to the solar cells that have the highest η values at the end of the light soaking experiment, without considering the dots corresponding to solar cells with η < 5.5%. When no three dots corresponding to solar cells with η ≥ 5.5% could be selected out of the twelve available dots, less than three dots had to be used by necessity to calculate the average, resulting in some experimental irregularity for some samples. As discussed earlier in this section, the optical gap of the absorber layers does not change after light soaking, which explains why the Voc

† After a close inspection of the front cover of this thesis, it is possible to recognise the different back contacts on some of the investigated solar cells as groups of square dots, while the connections to the front contacts can be recognised as rectangular bars next to the dots.

102

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η 1.35 mbar 0.85 1.57 mbar 1.79 mbar 0.80 2.00 mbar (Al) 2.00 mbar (AgAl)

normalised 0.75 2.20 mbar 2.40 mbar R=0 reference (Al) 0.70 2.60 mbar R=0 reference (AgAl)

0 10 100 1000 10000 time (minutes)

Figure 6.3: Evolution in time of the external parameters of the solar cells with the R = 20 absorber layers deposited at different pressures and the reference solar cells with the R = 0 absorber layer. All external parameters are normalised to their initial values.

103 values of the solar cells with the R = 20 absorber layers do not change significantly during the light soaking experiment. The increase in Voc for the solar cell with the absorber layer deposited at 1.35 mbar is therefore most likely an experimental irregularity, since that particular solar cell had less than three good dots at the end of the light soaking experiment. This also explains the increase in FF for this solar cell after 80 minutes of light soaking. The R = 0 absorber layers do show a continuous degradation of the Voc during light soaking, which is likely to be related to the larger increase in Nd for the R = 0 absorber layers in comparison to the R = 20 absorber layers, possibly causing a barrier in the R = 0 absorber layer.

The increase in normalised Jsc and normalised η of all of the investigated solar cells after 320 minutes of light soaking could be explained by an unwanted increase of the ambient temperature in the degradation setup, causing the annealing effect on the light-soaked solar cells to be temporarily larger than the photo-induced degradation.

Secondly, the increase in normalised Jsc and normalised η could be attributed to intensity fluctuations of the solar simulator lamp. As this experimental irregularity affects all samples under investigation, it does not hinder the comparison between individual samples presented here. The difference in stability between the solar cells with the R = 20 absorber layers and the reference solar cells with the R = 0 absorber layer is clear: the normalised FF stabilises at 0.91 – 0.93 after ~10,000 minutes (or 173 hours) for all solar cells with R = 20 absorber layers, while the normalised FF of the reference solar cells with the R = 0 absorber layer reaches 0.87 – 0.88 after ~40,000 minutes (or 675 hours). Because of the stable FF for the solar cells with the R = 20 absorber layers after 173 hours, this moment has been chosen to perform the final round of FTPS measurements on all samples, since no significant changes in the α spectrum are to be expected after stabilisation of the FF. The solar cells with the Al back contacts and the R = 20 absorber layers reach normalised η values of 0.85 – 0.90 after ~40,000 minutes, while the normalised η value of the reference solar cell with the R = 0 absorber layer and the Al back contact is 0.79 after ~40,000 minutes. The normalised η of the reference solar cell with the R = 0 absorber layer and the AgAl back contact is even lower; this is attributed to a stronger degradation in solar cells with an AgAl back contact, as was already discussed earlier in this section. In summary, the solar cells with the R = 20 absorber layers are more stable against photo-induced degradation than the reference solar cell with an absorber layer deposited at R = 0, as is demonstrated by the higher stabilised normalised FF for the R = 20 solar cells. After stabilisation of the FF, the η continues to degrade, because of the continuous degradation of Jsc after ~10,000 minutes. This lack of stabilisation in the Jsc could be attributed to a decreasing reflectance of the back contact due to metal diffusion from the back contact into the silicon upon heating [121]. Another possible explanation is that the lamp of the solar simulator degraded over the course of the light soaking experiment and its intensity decreased, resulting in a continuously decreasing trend for the normalised Jsc. To get a better understanding of the degradation of the Jsc after stabilisation of the FF, a second light soaking experiment has been performed, which will be discussed in detail in section 6.6.

104

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R=20 absorber layers 0.59 initial: Al initial: AgAl after 1.3 hours: Al 9.0 after 1.3 hours: AgAl after 173 hours: Al after 173 hours: AgAl 8.0

R=0 reference

(%) initial: Al

η 7.0 initial: AgAl after 1.3 hours: Al after 1.3 hours: AgAl 6.0 after 173 hours: Al after 173 hours: AgAl 1.4 1.6 1.8 2.0 2.2 2.4 2.6 pressure (mbar)

Figure 6.4: External parameters of the solar cells with the R = 20 absorber layers deposited at different pressures and the reference solar cells with the R = 0 absorber layer as a function of the deposition pressure at three different moments during the light soaking experiment.

105

The behaviour of the external parameters during light soaking as a function of the deposition pressure is depicted in figure 6.4. As was already clear from figure 6.2, the effect of the deposition pressure on the initial performance of the solar cell does not change during light soaking. Both before and after light soaking, higher pressures yield higher η and

FF, just as higher pressures result in lower Nd values. Because the Jsc values of the solar cells with the diluted absorber layer are both before and after light soaking ~12% lower than the Jsc of the R = 0 reference solar cell due to the band gap differences between the R = 0 and the R = 20 absorber layers, the absolute values of η and FF of the solar cells with the R = 20 absorber layers cannot be directly compared to the η and FF of the reference solar cells with the R = 0 absorber layer. Moreover, for the R = 20 solar cells, Voc ≈ 0.86 V and does not degrade significantly, while the Voc of the R = 0 reference solar cell degrades from 0.84 V to 0.81 V. Only the solar cell with the absorber layer deposited at 1.35 mbar has a lower Voc of 0.80 V, but it has already been discussed earlier that this particular solar cell had very few good dots at the end of the light soaking experiment. However, it can be concluded that within the R = 20 pressure series with the Al back contact, the solar cells with the highest η and FF are deposited at pressures between 2.20 mbar and 2.60 mbar: the highest stabilised η is 7.0% and the highest stabilised FF is 0.65. For the reference solar cell, a degradation of the η from 8.7% to 7.1% and a degradation of the FF from 0.71 to 0.63 are observed after ~10,000 minutes of light soaking without any sign of stabilisation. With respect to the solar cells with the AgAl back contact, it can clearly be seen that the degradation is larger than it is for the solar cells with the same absorber layer and the Al back contact. This is in line with the earlier observed difference in the increase of Nd of the solar cells with the two different back contact configurations during light soaking. However, the η values of the solar cells with the AgAl back contacts are still higher than the η values of the solar cells with the Al back contacts at the end of the light soaking experiment. Since the solar cells with the AgAl back contact continue to degrade after ~40,000 minutes, it can thus be expected that these solar cells will have a lower η than the solar cells with the Al back contact when the light soaking experiment would have been continued for more than ~40,000 minutes. Therefore, the use of an Al back contact is recommended over the use of AgAl back contact. Because the differences between the solar cells with the two different back contact configurations have now been reviewed sufficiently, it is not considered necessary to further discuss the solar cells with the AgAl back contacts in sections 6.3 – 6.5. Instead, it will only be attempted to identify the optimal value for each of the varied deposition parameters after light soaking.

6.3 Degradation of the rf-power series After the evaluation of the series of films and corresponding solar cell absorber layers deposited at different rf-powers in section 5.3, the results of the rf-power series after light soaking will be evaluated in this section. This evaluation will be done in the same way as the results of these series were discussed in section 5.3, but not as extensively as in the previous

106 section of this chapter. In fact, the only remaining purpose of this section is to investigate how the films and absorber layers deposited at different rf-powers behave during light soaking and whether the earlier determined optimal value of 4 W is still the optimal rf-power value after light soaking. Firstly, the α spectra of the films and the absorber layers are determined at three different moments during the light soaking experiment: initially, after 1.3 hours, and after 173 hours. The initial α spectra are equal to those discussed in section 5.3. As the typical changes in the α spectra for both an amorphous film and a film with a substantial crystalline fraction have already been illustrated in section 6.2, it is not considered interesting to display all the α spectra of the films and absorber layers deposited at different rf-powers during the light soaking experiment. It is more useful to directly review the changes in Nd for the films and absorber layers during light soaking, since the degradation of each individual sample within the series of films and absorber layers cannot be accurately monitored when only the α spectra would be displayed. The resulting Nd versus rf-power plots are illustrated in figure 6.5.

R=20 films initial after 1.3 hours 1016 after 173 hours

R=0 reference )

-3 initial after 1.3 hours

(cm after 173 hours d N

1015

R=20 absorber layers initial after 1.3 hours 1016 after 173 hours

R=0 reference )

-3 initial after 1.3 hours

(cm after 173 hours d N

1015

4 6 8 10121416 power (W)

Figure 6.5: Defect density as a function of rf-power of films and corresponding solar cell absorber layers obtained from their α spectra at three different moments during the light soaking experiment.

107

Just as for the pressure series, there is no dependence of the degradation rate on the rf-power, since the relative increase in Nd is comparable for all R = 20 films and absorber layers. Further, no difference between the degradation of the films and the degradation of the absorber layers can be seen. As was already demonstrated in the previous section, the R = 0 film and absorber layer show a larger relative degradation when compared to the R = 20 films and absorber layers. From the Nd plots, it can thus be concluded that, also after 173 hours of light soaking, the lowest rf-power in the investigated range results in the highest material quality, since the

Nd value of the absorber layer deposited at an rf-power of 4 W remains the lowest Nd value within the investigated series of absorber layers after light soaking.

To further confirm this result appearing from the analysis of the Nd plots, repeated JV measurements have been performed during the light soaking experiment on the solar cells with the absorber layers deposited at different rf-powers. Firstly, to investigate the relative degradation of the different solar cells, the external parameters of these solar cells as a function of the light soaking time are depicted in figure 6.6. All external parameters have been normalised to their initial value to be able to compare the relative degradation of the solar cells. It seems that there is no dependence of the degradation rate on the rf-power used for depositing the absorber layer of a solar cell, as the external parameters of all R = 20 absorber layers considered here evolve in a comparable manner during the light soaking experiment. The increase in Voc over time of the solar cell with an absorber layer deposited at 13.5 W may seem an abnormality, but this increase is mainly caused by the low initial Voc value for this solar cell (see figure 5.14), possibly due to insufficient annealing before performing the initial JV measurement, as was already discussed in section 5.3. The increase in Voc for this solar cell can then be understood as an annealing process occurring in the first stages of the light soaking experiment, after which no significant changes in the Voc can be recognised. Further, an increase in all normalised Jsc values can be seen after 320 minutes of light soaking. This experimental irregularity affects all samples under investigation and does therefore not hinder comparisons between the absorber layers within the same series, as has been discussed already in section 6.2. Finally, it can again be stated that the R = 20 absorber layers are more stable against light soaking than the reference R = 0 absorber layer, since the FF of the R = 20 solar cells stabilises after ~10,000 minutes, while the R = 0 absorber layer has not stabilised yet after ~40,000 minutes of light soaking. After stabilisation of the FF, there is however no stabilisation of the Jsc, which will be discussed in more detail in section 6.6. The behaviour of the external parameters during the light soaking experiment as a function of the rf-power used for depositing the absorber layer of the solar cell is depicted in figure 6.7. As was already clear from figure 6.6, the effect of the rf-power used for the deposition of the absorber layer on the initial performance of the solar cell does not change during light soaking. An exception to this trend is formed by the absorber layer deposited at 16 W, which stabilises earlier than the other absorber layers. However, the absorber layer deposited at 16 W has relatively high

Nd and EU values (see section 5.3) and is therefore not considered to consist of high-quality material, which is further reflected by the low FF of

108

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0.85 4.0 W 7.2 W 10.3 W 0.80 13.5 W normalised 16.0 W 0.75 R=0 reference

0 10 100 1000 10000 time (minutes)

Figure 6.6: Evolution in time of the external parameters of the solar cells with the R = 20 absorber layers deposited at different rf-powers and the reference solar cell with the R = 0 absorber layer. All external parameters are normalised to their initial values.

109

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R=20 absorber layers 8.0 initial after 1.3 hours 7.0 after 173 hours (%) η 6.0 R=0 reference initial 5.0 after 1.3 hours after 173 hours 46810121416 power (W)

Figure 6.7: External parameters of the solar cells with the R = 20 absorber layers deposited at different rf-powers and the reference solar cell with the R = 0 absorber layer as a function of the rf-power at three different moments during the light soaking experiment.

110 the solar cell containing this absorber layer. As the degradation rate is further not affected by the rf-power used for the deposition of the absorber layer, it still holds that the solar cells with the highest performance within this series contain an absorber layer that has been deposited using a low rf-power. More specifically, the solar cell with the absorber layer deposited at 4 W is, both before and after light soaking, the solar cell with the highest performance within this series.

6.4 Degradation of the silane flow series After the evaluation of the series of films and corresponding solar cell absorber layers deposited using different silane flows in section 5.4, the results of the silane flow series after light soaking will now be evaluated.

Firstly, the increase in Nd during the light soaking experiment for all films and absorber layers deposited using different silane flows will be discussed. The Nd values for all these samples as a function of the silane flow are depicted in figure 6.8. From this figure, it can be seen that the increase in Nd – and thus the degradation – evolves similarly for the series of films and absorber layers deposited using different silane flows. This means that the silane flow does not greatly affect the degradation rate.

Both before and after light soaking, a roughly constant trend in the Nd plots can be seen, except for the slight increase in Nd with increasing silane flow for silane flows above 5 sccm. To verify whether also for this series of samples the degradation rate does not depend on the varied deposition parameter, the external parameters obtained from JV measurements performed during the light experiment should be considered. Firstly, the evolution in time of the external parameters of the solar cells with absorber layers deposited using different silane flows is presented in figure 6.9. Just as was the case for the rf-power series discussed in the previous section, there is one solar cell in the silane flow series that has probably not annealed sufficiently before the start of the light soaking experiment. It should be clear from the evolution of Voc in time of the different solar cells that this is the solar cell with the absorber layer deposited using a silane flow of 3 sccm. Again all solar cells with R = 20 absorber layers seem to degrade similarly, but when the normalised FF is closely inspected, some minor differences in the degradation rate within the series can be seen. Especially the solar cell with the absorber layer deposited at a silane flow of 1 sccm seems to stabilise at a slightly higher normalised FF than the other solar cells with an R = 20 absorber layer (0.94 versus ~0.92). Because this difference is rather small and the absorber layer deposited at a silane flow of 1 sccm does not show abnormal values for E04, ET, EK, EU, or Nd, it is likely that there are no significant differences in the material quality of the different absorber layers. Instead, it is possible that there was a problem with the deposition of the p-layer of the solar cell with the absorber layer deposited using a silane flow of 1 sccm. To further investigate the external parameters during light soaking, the external parameters as a function of the silane flow are depicted as a function of the silane flow in figure 6.10. Now, when inspecting the plots of Voc and Jsc, there appears to be no dependence of the degradation rate on the silane flow, but in the plot of the FF such a dependence can be

111

R=20 films initial after 1.3 hours 1016 after 173 hours

R=0 reference )

-3 initial after 1.3 hours

(cm after 173 hours d N

1015

R=20 absorber layers initial after 1.3 hours 1016 after 173 hours

R=0 reference )

-3 initial after 1.3 hours

(cm after 173 hours d N

1015

12345678910 SiH flow (sccm) 4

Figure 6.8: Defect density as a function of silane flow of films and corresponding solar cell absorber layers obtained from their α spectra at three different moments during the light soaking experiment.

seen, albeit not a very clear one. Especially the relative degradation of the solar cells with absorber layers deposited at 1 sccm and 10 sccm respectively show a smaller and a larger relative degradation than the other solar cells within this series. As it has already been discussed earlier, there are no indications that the quality of the absorber layers within this series are different and it cannot be understood why the absorber layers deposited at silane flows of 1 sccm and 10 sccm would show a different relative degradation when compared to the other absorber layers. Moreover, the differences in relative degradation between the absorber layers within this series are so small that it is unlikely that there is indeed a different dependence of the quality of the absorber layer on the silane flow, both before and after light soaking. Therefore, the slightly decreasing trend in FF and η for increasing silane flow that can be seen in figure 6.10 should be interpreted as a constant trend and when this series of solar cells would be deposited again, it is questionable whether this decreasing trend would be reproduced. Concluding, it can

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0.85 1.0 sccm 3.0 sccm 5.0 sccm 0.80 7.5 sccm normalised 10.0 sccm 0.75 R=0 reference

0 10 100 1000 10000 time (minutes)

Figure 6.9: Evolution in time of the external parameters of the solar cells with the R = 20 absorber layers deposited at different silane flows and the reference solar cell with the R = 0 absorber layer. All external parameters are normalised to their initial values.

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R=20 absorber layers initial 8.0 after 1.3 hours after 173 hours (%)

η 7.0 R=0 reference initial 6.0 after 1.3 hours after 173 hours 12345678910 SiH flow (sccm) 4

Figure 6.10: External parameters of the solar cells with the R = 20 absorber layers deposited at different silane flows and the reference solar cell with the R = 0 absorber layer as a function of the silane flow at three different moments during the light soaking experiment.

114 thus be said that after the light soaking experiment, the solar cell with the absorber layer deposited at 3 sccm appears to have the highest FF and η values and the quality of the absorber layer slightly decreases for increasing silane flow. However, the difference between the highest and lowest FF and η values is so small that it is better to state that there is in fact no dependence of the degradation rate on the silane flow. When this is assumed, both before and after light soaking, there are no significant quality differences within this series of absorber layers and every silane flow in the investigated range results in an equal quality of the deposited absorber layer.

6.5 Degradation of the substrate temperature series The last series of films and corresponding solar cell absorber layers that will be discussed, are those deposited at different substrate temperatures. As a continuation of section 5.5, the results of the substrate temperature series after light soaking will now be discussed. Firstly, the changes in Nd as a function of the substrate temperature during the light soaking experiment of both the films and absorber layers are illustrated in figure 6.11. From this figure, it can be seen that the relative degradation is comparable for all films and absorber layers, with the exception of the film deposited at 200 °C. The relative degradation for this film is notably smaller than it is for the other films, which can be understood by considering its crystalline fraction. As discussed earlier in section 6.2, the relative degradation of crystalline material is smaller than the relative degradation of amorphous material. Since all other films and absorber layers degrade similarly, the increasing trend in Nd for increasing substrate temperature is maintained after light soaking. Using a substrate temperature of 150 °C during the deposition of the films and absorber layers still results in the material with the lowest Nd value, and thus with the highest quality. To further verify this result, the evolution in time of the normalised external parameters of the solar cells with the absorber layers deposited at different substrate temperatures should be considered. This is achieved by means of repeated JV measurements that have been performed during the light soaking experiment. The resulting plots of the external parameters as a function of the light soaking time are depicted in figure 6.12. From this figure, it is directly clear that there are no differences in relative degradation within the series of absorber layers deposited at different substrate temperatures. Further, note that the solar cells deposited at 150 °C and 200 °C did not have any good dots left at the end of the light soaking experiment, which explains the strong decrease in FF for these solar cells after ~20,000 minutes of light soaking. When comparing figure 6.12 to the evolution of the normalised external parameters in the previous three sections of this chapter (see figure 6.3, figure 6.6, and figure 6.9) it can be seen that for the substrate temperature series, no increase of the external parameters after 320 minutes can be seen. As this light soaking experiment was started one week after the start of the light soaking experiment for the pressure, rf- power, and silane flow series, it is further confirmed that the increase of the external parameters after 320 minutes of light soaking for the latter

115

R=20 films initial 17 10 after 1.3 hours after 173 hours

R=0 reference )

-3 initial 1016 after 1.3 hours

(cm after 173 hours d N

1015

R=20 absorber layers initial after 1.3 hours 1016 after 173 hours

R=0 reference )

-3 initial after 1.3 hours

(cm after 173 hours d N

1015

150 160 170 180 190 200 temperature (oC)

Figure 6.11: Defect density as a function of substrate temperature of films and corresponding solar cell absorber layers obtained from their α spectra at three different moments during the light soaking experiment.

three series of solar cells is due to an experimental irregularity, as was already suggested in section 6.2. Further, it seems that the evolution in time of the external parameters of the substrate temperature series during light soaking shows less scatter in the external parameter data than can be seen for the other three series of solar cells. This can be understood by the different manner in which the solar cells have been handled during the JV measurements. The solar cells of the pressure, rf- power, and silane flow series have been simultaneously removed from and replaced in the degradation setup when JV measurements had to be performed, while the solar cells of the substrate temperature series have been removed from and replaced in the degradation setup one by one. In this way, the time during which the solar cells are not exposed to the light in the degradation setup is minimised, which reduces the influence of room temperature annealing on e.g. the evolution of the FF in time. Additionally, the solar cells of the substrate temperature series have been dipped in demineralised water at room temperature for a few seconds

116

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0.95

0.90 (-) η 150 oC 0.85 o 160 C o 0.80 170 C 180 oC 190 oC normalised 0.75 200 oC 0.70 R=0 reference

0 10 100 1000 10000 time (minutes)

Figure 6.12: Evolution in time of the external parameters of the solar cells with the R = 20 absorber layers deposited at different substrate temperatures and the reference solar cell with the R = 0 absorber layer. All external parameters are normalised to their initial values.

117

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0.87 (V) oc V 0.84

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R=20 absorber layers initial 8.0 after 1.3 hours after 173 hours (%)

η 7.0 R=0 reference initial 6.0 after 1.3 hours after 173 hours 150 160 170 180 190 200 temperature (oC)

Figure 6.13: External parameters of the solar cells with the R = 20 absorber layers deposited at different substrate temperatures and the reference solar cell with the R = 0 absorber layer as a function of the substrate temperature at three different moments during the light soaking experiment.

118 immediately after they had been removed from the degradation setup to perform a JV measurement. The reason for treating the solar cells like this is that in such a way the solar cells cool down faster when they are taken out of the degradation setup, which further minimises the influence of low temperature annealing during the time when the solar cells are not inside the degradation setup. To prevent the water from corroding the metal contacts, every solar cell has to be dried thoroughly using e.g. compressed air after the solar cell is taken out of the water. When the solar cell is properly dried, the water does not affect the solar cell’s performance or material properties. To verify that the water has no influence on the solar cell’s performance, a solar cell has been placed in the water for several minutes. Only after having left the solar cell in demineralised water for 30 minutes, the first small change in the external parameters was found, so it is very likely that holding a solar cell in demineralised water for 5 – 10 seconds does not affect the performance of the solar cell, and even more when the solar cells are always properly dried when they are taken out of the water. This different treatment of the solar cells can also be recognised as the cause for the earlier stabilisation of the FF of the solar cells from the substrate-temperature series when compared to the solar cells from the other three series (720 minutes versus ~10,000 minutes) that were discussed in the previous sections of this chapter. As has been observed for the evolution in time of the external parameters of the pressure, rf-power, and silane flow series, also for the substrate temperature series, it can be seen that after stabilisation of the FF, the Jsc continues to decrease. To further investigate this recurring abnormality, it will be discussed, in section 6.6, whether or not this can be attributed to diffusion of the back contact into the silicon, as was earlier suggested in section 6.2. After having considered the relative degradation of the external parameters in time, the external parameters are presented as a function of the substrate temperature in figure 6.13. Again, it can be seen that the degradation is comparable for all solar cells and does not depend on the substrate temperature, with the exception of the solar cell with the absorber layer deposited at 200 °C, as has already been discussed earlier in this section. This means that also after light soaking, lower substrate temperatures result in a higher quality of the deposited material. For this reason, the solar cell with the absorber layer deposited at 150 °C remains the solar cell with the best performance after light soaking within this series of solar cells.

6.6 Degradation of the Jsc after stabilisation of the FF As has been seen in the previous four sections, there is a continuous degradation of the Jsc after stabilisation of the FF after 173 hours of light soaking for the solar cells with the different R = 20 absorber layers. Possibly, as has been suggested in section 6.2, this is due to a diffusion of the metal of the back contact into the n-layer of the solar cell, which results in a decreased reflection of the back contact. This idea is inspired by an earlier performed annealing experiment performed at 150 °C [121]. In this experiment, there is a strong decrease in reflectance from an AgAl and an Al layer (both deposited on top of a silicon layer), already after 30

119 minutes of annealing. However, the used annealing temperature is much higher than the temperature of 50 °C at which the light soaking experiment has been performed, so it is not certain whether this reflectance decrease also occurs in the back contact of a solar cell within the time frame of the light soaking experiment. To verify whether or not there is a notable decrease in the reflectance from the back contact during light soaking, the back side of a solar cell has been deposited individually on Corning glass. The considered configurations are:

• Corning / n-type a-Si:H (20 nm) / Al (300 nm), • Corning / n-type a-Si:H (20 nm) / Ag (100 nm) / Al (200 nm), • Corning / n-type a-Si:H (20 nm) / ZnO (80 nm) / Al (300 nm), • Corning / n-type a-Si:H (20 nm) / ZnO (80 nm) / Ag (100 nm) / Al (200 nm).

The first two configurations are equal to the back sides of the solar cells with the Al and the AgAl back contacts that were discussed previously (see section 5.1.2). The other two configurations with the extra ZnO layer are additionally included in this new light soaking experiment to see whether or not this ZnO layer can suppress the supposed diffusion of the metal into the n-layer. These four samples are consequently cut into two pieces, so two experiments on effectively the same four samples can be performed simultaneously. One half of each of the four samples is light-soaked under the same conditions as the solar cells from the previous sections in this chapter: an irradiance of 1,000 W/m2 at a temperature of 50 °C. At the same time, the other halves of the samples are annealed in an oven at 50 °C. By exposing only one half of each sample to the light in the degradation setup, it can be verified not only whether there is a reflectance decrease during light soaking, but also whether the supposed decrease in reflectance is predominantly a light effect or a heat effect. Since the reflectance is supposed to decrease due to metal diffusion, it is expected that the reflectance decrease is predominantly a heat effect. To further simulate the conditions to which the solar cells have been exposed, only the two samples without an Ag layer have been annealed at 130 °C for 30 minutes, before starting the new light soaking and annealing experiment of the above-described four samples. To monitor the reflectance during the light soaking and annealing experiments, an RT measurement system has been used. The resulting reflectance spectra, recorded at several different moments during the two experiments, are depicted in figure 6.14. From this figure, it is immediately clear that in both experiments, none of the samples shows any decrease in reflectance. Even after 1,421 hours of light soaking and annealing at 50 °C, no significant decrease in the reflectance can be seen for any of the four samples. For this reason, metal diffusion into the n- layer, or any other effect possibly causing a reflectance decrease from the back contact, cannot be identified as the reason for the continuously degrading Jsc after stabilisation of the FF. Also, the continously decreasing Jsc after 173 hours of light soaking cannot be explained by a change somewhere in the p-i-n structure of the solar cell, as the FF has then stabilised. Therefore, the decreasing Jsc is explained not by a change of the material properties of the solar cell, but by a change in the JV

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1.0

0.8 n + Al as deposited 0.6 annealed after 1.3 hours after 173 hours 0.4 after 1421 hours reflectance (-) 0.2 n + AgAl o as deposited annealing at 50 C 0.0 after 1.3 hours after 173 hours after 1421 hours 1.0

n + ZnO + Al 0.8 as deposited annealed 0.6 after 1.3 hours after 173 hours after 1421 hours 0.4

reflectance (-) n + ZnO + AgAl 0.2 as deposited after 1.3 hours light soaking at 50 oC 0.0 after 173 hours after 1421 hours 400 500 600 700 800 900 1000 wavelength (nm)

Figure 6.14: Reflectance spectra of four different configurations of the back part of a solar cell at four different moments during the light soaking and annealing experiments. Note that only for the samples with an Al layer, an extra annealing step of 30 minutes at 130 °C has been performed at the start of these experiments, since this also has been done for the solar cells with an Al back contact.

measurement conditions. As Jsc is proportional to the intensity of the light that illuminates a solar cell during a JV measurement, the impression arises that the intensity of the lamp in the solar simulator decreased over the course of the light soaking experiment of the solar cells that was discussed earlier in this chapter. To set the intensity of the lamp of the solar simulator to the correct value at the start of the light soaking experiment, a silicon photodiode has been used. However, during the light soaking experiment, this intensity has not been changed to preserve the same illumination conditions for each JV measurement, but probably the intensity of the lamp decreased due to the large number of required burning hours. Further, the photodiode cannot be safely used to calibrate the intensity of the solar simulator lamp to the correct value at the start of each JV measurement, as the photocurrent readout is strongly

121 temperature-dependent. When the photodiode is repeatedly used to measure the intensity of the solar simulator lamp, the photodiode heats up and therefore overestimates the intensity of the lamp. For this reason, it is advisable to use a commercial luxmeter instead of a simple photodiode to monitor the intensity of the lamp of the solar simulator, because a luxmeter is usually equipped with a protective cap placed over the photodetector which can diminish the effect of heating on the photodetector.

6.7 Outdoor experiment As has been observed in section 6.2 (and the three sections following thereafter), there is a large difference in the stability against photo- induced degradation for solar cells with absorber layers deposited at R = 0 when compared to solar cells with absorber layers deposited at R = 20. It has thus become clear that the use of hydrogen-diluted silane for the deposition of the absorber layer in a solar cell is beneficial for the stability of the solar cell against light soaking. This is especially clear when the normalised external parameters of an R = 20 solar cell are compared to the normalised external parameters of an R = 0 solar cell (see e.g. figure 6.3). However, this result has been obtained in ideal lab conditions with a constant irradiance over the course of a day. Of course, this is not a realistic representation of the outside world, where the power generated by a solar cell periodically varies over the course of 24 hours. This gives rise to the idea that perhaps, in outdoor conditions, the stabilised lab values for e.g. FF and η would not be achieved, since there is photo- induced degradation at daytime and (low-temperature) annealing at night. If these effects are of the same magnitude, which could be the case in the summer when the nights are relatively warm, it is questionable whether or not the stabilised lab values for FF and η would be reached due to repeated annealing during the nights. To investigate this possibility, the reference R = 0 and R = 20 solar cells, which have been repeatedly discussed in the previous sections of this chapter, have been deposited again to monitor their behaviour in outdoor conditions. These solar cells have been placed outside on the roof to prevent shadows from e.g. trees from falling on the solar cells. Further, to protect the solar cells from dirt and moist, they have been mounted on the inside of a transparent lid of a plastic box. Since this transparent lid absorbs a certain part of the sunlight before it can reach the solar cells, the lid has been partly replaced by a piece of Corning glass. To verify whether there are indeed repeated degradation and annealing effects in the absorber layers, JV measurements have been performed three times per day over the course of one working week. The resulting plots of the normalised external parameters as a function of the time are depicted in figure 6.15. To compare the results from the outdoor experiment to the results from the indoor light soaking experiment performed in lab conditions, the evolution in time of the external parameters obtained from the indoor experiment have been included in the figure as well. Note that the external parameters obtained from the indoor experiment have been taken from the analysis of the same R = 0 and R = 20 reference solar cells (see figure 6.3) as the solar cells that are

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1.06 outdoor indoor R=0 R=0 1.04 R=20 R=20 (-)

oc 1.02

1.00

0.98 normalised V 0.96

1.00

0.99 (-)

sc 0.98

0.97

0.96 normalised J 0.95

1.04

1.00

0.96

0.92 normalised FF (-) 0.88

1.00

0.96 (%) η 0.92

0.88 normalised 0.84

012345 time (days)

Figure 6.15: Evolution in time of the external parameters of a solar cell with an R = 20 absorber layer and a solar cell with an R = 0 absorber layer during both the outdoor experiment and the indoor experiment. In this context, “indoor” refers to the light soaking experiment discussed in the previous sections of this chapter. All external parameters are normalised to their initial values. Note that each integer value on the time axis corresponds to midnight.

123 investigated in the outdoor experiment. Further, note that the absolute values of the external parameters are not depicted here, as they have already been discussed several times before in this chapter. For the outdoor experiment, it cannot easily be seen whether the supposed degradation and annealing effect over the course of 24 hours is present in the evolution in time of the external parameters. This is because the irradiance and temperature fluctuate very irregularly during a single day and also from one day to another. These irregularities are clearly illustrated in figure 6.16 and are the reason for the strong fluctuations of mainly the Jsc and FF of the R = 0 solar cell. For the R = 20 solar cell, the fluctuations in Jsc and FF are much smaller, as the absorber layer of this solar cell is more stable against light soaking.

When closely inspecting the evolution in time of the Voc of the R = 0 solar cell, it seems that the expected trend can be seen: degradation (decrease) during the day and annealing (increase) at night. However, this trend is not at all clear from the evolution in time of the Jsc and the FF, so it has to be concluded that there is indeed annealing at night, but it is much smaller than the overall degradation of the absorber layers over the course of five days. Because the annealing effect is very small in

40 C) o

20 temperature ( 10

1200 ) 2 900

600

300 irradiance (W/m 0

012345 time (days)

Figure 6.16: Temperature and irradiance variations during the outdoor experiment. The irradiance values have been obtained from measurements with a pyranometer. Note that the temperature values depicted here do not correspond to the ambient temperature, but to the temperature on the back side of some crystalline module located next to the plastic box containing the R = 0 and R = 20 solar cells. It has been verified that the temperature inside the plastic box is comparable to the temperature on the back side of the module.

124 comparison to the degradation effect in the evolution in time of the external parameters, it is likely that the same stable values for the external parameters would eventually be reached in both the indoor and the outdoor experiment. Therefore, it was not considered useful to continue the outdoor experiment until this stable point had been reached. Further, it can be concluded that the evolution in time of the external parameters in the indoor experiment is much smoother than it is in the outdoor experiment, due to the fluctuating wheather conditions. For possible future outdoor experiments, the wheather conditions should be strictly controlled and monitored, i.e. better than in this outdoor experiment. For as long as this cannot be achieved, indoor experiments are preferred over outdoor experiments.

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7 Conclusions and recommendations In this final chapter, an overview is given of the most important findings from this thesis. In section 7.1, the main conclusions are presented, and in section 7.2, several recommendations for future work are included. Note that these are just the highlights from the previous chapters and the lists of conclusions and recommendations are thus not complete.

7.1 Conclusions Concerning FTPS, the following main conclusions can be drawn:

• FTPS is a useful tool to monitor the defect density during light soaking of both Si:H thin films and solar cell absorber layers. • FTPS is an accurate measurement method, as has been verified by comparative DBP measurements. • FTPS has been successfully used to detect the structural phase of Si:H films and absorber layers.

Regarding the optimisation of the deposition parameters of the absorber layer, the following can be concluded:

• The highest material quality of films and absorber layers deposited using a hydrogen-to-silane dilution ratio of 20 is achieved for a high deposition pressure (2.60 mbar), a low rf-power (4 W), and a low substrate temperature (150 °C). • All silane flows between 1 sccm and 10 sccm deposited using a hydrogen-to-silane dilution ratio of 20 result in an equal quality of the deposited films and absorber layers. • The degradation rate for both films and absorber layers is not dependent on the deposition pressure, the rf-power, the silane flow, or the substrate temperature used for the deposition of the absorber layer. • An increased stability against light soaking is observed for films and absorber layers deposited using a hydrogen-to-silane ratio of 20 when compared to a film and absorber layer deposited from undiluted silane. For all investigated solar cells with absorber layers deposited at a hydrogen-to-silane dilutuion ratio of 20, the relative degradation of the fill factor is only ~8%.

7.2 Recommendations for future work Concerning FTPS, the following recommendations can be made:

• To shorten the measurement time and increase the accuracy of the obtained values in the photocurrent spectrum, it is advisable to mount the system on an optical table to diminish the influence of mechanical vibrations. • For convenience purposes, the FTPS measurement system should be fully automated, meaning that the five different measurements

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with the different optical filters in the FTIR spectrometer, of which one full FTPS measurement typically consists, should no longer have to be started manually. • A laser with a lower wavelength (e.g. a green laser) should be installed in the FTIR spectrometer instead of the currently present red laser which is used to control the velocity of the moving mirror in the FTIR spectrometer. When a laser with a lower wavelength is used, the photocurrent spectrum obtained from an FTPS measurement extends to higher photon energies, since the laser wavelength determines the maximum photon energy up to which an FTPS measurement can be performed without resulting in aliasing. When the photocurrent spectrum extends to higher photon energies, it is easier to perform the required normalisation to the absorption coefficient spectrum obtained from an RT measurement.

Regarding the material properties of the absorber layer, the following recommendations for further research can be made:

• Determine whether the obtained set of deposition parameters used for depositing the absorber layer is not a sub-optimal set for the used hydrogen-to-silane dilution ratio of 20. • Investigate whether the observed increase in quality can be improved by further increasing the pressure, lowering the rf-power, and lowering the substrate temperature. • As the silane flow does not affect the quality of the deposited absorber layer, a silane flow of less than 5 sccm can be used to be able to deposit amorphous films and absorber layers at a hydrogen- to-silane ratio higher than 40. This hydrogen-to-silane dilution ratio is currently the maximum value that can be achieved when a silane flow of 5 sccm is used, because the hydrogen flow cannot be higher than 200 sccm due to a physical limitation of the particular PECVD system. • Perform a similar optimisation of the deposition parameters used for depositing the absorber layer as presented in this thesis for a hydrogen-to-silane ratio lower than 20, to investigate whether it is possible to obtain absorber layers that show a similar relatively small degradation during light soaking as the absorber layers discussed in this thesis, yet with higher initial values for the fill factor and conversion efficiency. • Combine the results from the optimisation of the deposition parameters of the a-Si:H absorber layer with the results from a similar optimisation of the deposition parameters of a μc-Si:H absorber layer to create the first micromorph tandem solar cell at Delft University of Technology.

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Appendices

Appendix A: MATLAB script used for processing FTPS data In this appendix, the MATLAB script that is used for creating a relative photocurrent spectrum from the FTPS measurement data is presented. The script is supplied with extensive comments, making it self- explanatory. Note that the script has been written in MATLAB version 7.1 (release 14) and, because the so-called cell mode is used, it is not possible to run the script on MATLAB versions lower than 7.1.

% Relative photocurrent / absolute absorption coefficient spectrum % calculation using FTPS data % % Version 1.0 % September 15, 2006 % M. Verbaan % [email protected] % % Version 2.0 % May 3, 2007 % J. Melskens % [email protected]

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % This script creates a relative photocurrent (or absolute % % absorption coefficient) spectrum from FTPS (and RT) data by: % % % % * Correcting the FTPS measurements for the background measured by % % the DTGS detector. % % * Correcting the background measurement for the frequency % % dependence of the DTGS detector. % % * Correcting the background measurement for the energy dependence % % of the DTGS detector. % % * Correcting the FTPS measurements for the frequency dependence % % of the a-Si detector (the sample under investigation). % % * Scaling the corrected FTPS data to the absorption coefficient % % spectrum obtained from an RT measurement (if OPTA will be used % % to do this, the FTPS absorption data are scaled to a dummy % % value for plotting purposes). % % * Selecting from each of the five FTPS photocurrent spectra (each % % measured with a different filter in the FTIR spectrometer) the % % correct energy range and connecting them. % % * Connecting the combined FTPS photocurrent spectrum to the % % absolute absorption coefficient spectrum if OPTA is not % % selected to do this and storing the data in a comma-separated % % *.ftps file and the spectrum itself in an *.emf file % % (optional). % % * Storing the combined photocurrent spectrum data values in an % % *.ftps.dbp file, imitating the syntax of a regular *.dbp file, % % and the spectrum itself in an *.emf file (optional) if OPTA % % will be used to connect the combined photocurrent spectrum to % % the absolute absorption coefficient spectrum obtained from RT. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

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clear('all'); close('all');

%% ****************************************** %% %% *** PART 1/10: OBLIGATORY SAMPLE INPUT *** %% %% ****************************************** %%

% Use OPTA or MATLAB to scale the photocurrent spectrum obtained from % an FTPS measurement to the absorption coefficient spectrum obtained % from an RT measurement? OPTA: use_OPTA = 1, MATLAB: use_OPTA = 0. % Because MATLAB does not remove the interference from the absorption % coefficient spectrum, the default value is 1. use_OPTA = 1;

% Define an array of samples for which the photocurrent spectrum has % to be calculated from the FTPS data with this script. The columns % of this array represent (respectively in ascending order) the % sample names, the directories containing the FTPS measurement data, % the directories containing the background measurement data, the % directories where the output of this script has to be stored, the % values of the variable highest_filter (for an explanation of this % variable see PART 4/10: PRE-PROCESSING INPUT DATA), and the sample % names of the corresponding layers on which the RT measurement has % been performed earlier (identical to the sample name in case of a % layer, but different in case of a cell; this column has to be % filled out only when use_OPTA = 0). samples_dir = 'C:\mydocs\TU Delft\Jaar 5\Thesis\Jimmy\data\'; samples_FTPS = 'ftps\'; samples_background = [samples_FTPS,'background\background ']; if (use_OPTA == 1) samples_output = 'alpha\with OPTA\'; else samples_output = 'alpha\without OPTA\'; end; samples_array = ... [cellstr('a2874') cellstr([samples_dir,samples_FTPS,'new_FTPS\a2874\']) cellstr([samples_dir,samples_background,'070622\']) cellstr([samples_dir,samples_output,'new_FTPS\']) 5 cellstr('a2844'); cellstr('a2874r2') cellstr([samples_dir,samples_FTPS,'new_FTPS\a2874r2\']) cellstr([samples_dir,samples_background,'070705\']) cellstr([samples_dir,samples_output,'new_FTPS\']) 5 cellstr('a2844'); ];

% Define which value(s) of highest_filter has / have to be used % during the calculation of the photocurrent spectrum. Use the value % of highest_filter as defined above in samples_array: % samples_type_highest_filter = 0; use all possible values of % highest_filter in order to be able to select the correct value of % highest_filter later on: samples_type_highest_filter = 1; use the % highest possible value for highest_filter: % samples_type_highest_filter = 2. Typical use of this script is to % first set samples_type_highest_filter equal to 1 to find the % correct value of highest_filter, after which this value is entered % in the 5th column of samples_array and samples_type_highest_filter

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% is set equal to 0 before the script is run again. The value of 2 % should only be used if it is certain that the optical filter with % the highest present cut-off wavelength (usually the Si filter) % should be used as highest_filter setting for all samples defined in % samples_array. samples_type_highest_filter = 0;

% Define the factor by which the number of data points forming the % photocurrent spectrum has to be reduced to be able to load this % spectrum in OPTA. The default value is 8, because this is the % minimum value required by OPTA and higher values will result in a % decrease of the resolution of the photocurrent spectrum. When the % photocurrent spectrum obtained from FTPS is scaled to the % absorption coefficient spectrum obtained from RT with MATLAB % (use_OPTA = 0), the reduction factor can be chosen as low as % possible, i.e. equal to 0, to avoid an unnecessary loss of % resolution in the spectrum. reduction_FTPS = 8;

% Save the calculated photocurrent spectrum to an *.emf file? Yes: % save_emf = 1, No: save_emf = 0. The default value is 1, since it is % necessary to review the relative photocurrent spectra after this % script has been run with samples_type_highest_filter = 1 to % determine the correct setting for highest_filter for each sample % defined in samples_array. save_emf = 1;

%% ****************************************** %% %% *** PART 2/10: DEFINITION OF CONSTANTS *** %% %% ****************************************** %%

% Wavelength-to-energy conversion factor: E = h * c / (eV_in_J * % lambda) = nm_to_eV / lambda where E is the energy in eV, h is % Planck's constant in J·s, c is the speed of light in m/s, eV_in_J % is the equivalent in J of 1 eV and lambda is the wavelength in nm. h = 6.6260693e-34; c = 299792458; eV_in_J = 1.60217653e-19; nm_to_eV = h * c / eV_in_J / 1e-9; clear h c eV_in_J;

% Define the maximum energy in eV up to which the data from the FTPS % measurement with a certain filter (RG645, RG695, FGL780, RG850 or % Si arc) is used. When use_OPTA == 0, this maximum energy specified % for the RG645 filter is the energy at which the photocurrent % spectrum obtained from an FTPS measurement is connected to the % absolute absorption coefficient spectrum obtained from an RT % measurement. The energy values are stored twice, so they can easily % be restored after an optional change later on, when it appears that % these maximum energies do not result in a smooth absorption % coefficient spectrum at the connecting energies. E_max_RG645 = 1.85; E_max_RG695 = 1.78; E_max_FGL780 = 1.59; E_max_RG850 = 1.46; E_max_Si = 1.00;

E_max_RG645_original = E_max_RG645; E_max_RG695_original = E_max_RG695; E_max_FGL780_original = E_max_FGL780;

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E_max_RG850_original = E_max_RG850; E_max_Si_original = E_max_Si;

% Define the colour of the plotted absorption coefficient spectrum. colour_FTPS = 'k';

%% ***************************************************** %% %% *** PART 3/10: START CALCULATING THE PHOTOCURRENT *** %% %% *** SPECTRUM *** %% %% ***************************************************** %%

% Determine the amount of samples defined in samples_array. samples_amount = length(samples_array(:,1));

% Calculate the photocurrent spectrum for all samples defined in % samples_array. for samples_counter = 1:samples_amount

% Clear the workspace except for the variables declared in the % preceding lines and close all figures. clear E_o* E_F* a* d* f* h* l* na* o* sc* st* w*; close('all');

% Store the sample name, the directory containing the FTPS % measurement data, the directory containing the background % measurement data and the directory where the output of this % script has to be stored for the current sample. name_sample = samples_array{samples_counter,1}; dir_FTPS = samples_array{samples_counter,2}; dir_background = samples_array{samples_counter,3}; dir_output = samples_array{samples_counter,4};

% Determine the number of present FTPS measurements performed % with the different FTIR spectrometer filters. if (exist([dir_FTPS,name_sample,' si.csv']) == 2) number_FTIR_filters_used = 5;

elseif (exist([dir_FTPS,name_sample,' rg850.csv']) == 2) number_FTIR_filters_used = 4;

elseif (exist([dir_FTPS,name_sample,' fgl780.csv']) == 2) number_FTIR_filters_used = 3;

elseif (exist([dir_FTPS,name_sample,' rg695.csv']) == 2) number_FTIR_filters_used = 2;

elseif (exist([dir_FTPS,name_sample,' rg645.csv']) == 2) number_FTIR_filters_used = 1; end;

% Initialise the following loop. samples_filter = 1;

% If the photocurrent spectrum of a sample has to be calculated % for all values of highest_filter (in order to determine the % correct value of highest_filter), meaning % samples_type_highest_filter == 1, the spectrum has to be % calculated five times (with each possible value of % highest_filter). For other values of

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% samples_type_highest_filter, the following loop is ended after % one execution. while (samples_filter <= number_FTIR_filters_used)

% Clear the workspace except for the variables declared in % the preceding lines and close all figures if % samples_type_highest_filter == 1. if (samples_filter > 1) clear E_o* E_F* a* f* h* l* o* sc* st* w*; close('all'); end;

%% ******************************************** %% %% *** PART 4/10: PRE-PROCESSING INPUT DATA *** %% %% ******************************************** %%

% Define which one of the optical filters that is to be used in the % calculation of the output has the highest cut-off wavelength. % RG645: highest_filter = 1, RG695: highest_filter = 2, FGL780: % highest_filter = 3, RG850: highest_filter = 4, Si: highest_filter = % 5. When a measurement with each of the five filters has been % performed and all five measurements have been performed well % enough, meaning that using e.g. the Si filter as the filter with % the highest cut-off wavelength does not give a more noisy % photocurrent spectrum than when the RG850 filter is used as the % filter with the highest cut-off wavelength for the calculation of % the output, the default value is 5. Any of the other four possible % values are only admitted if the uncertainty in the (low energy) % photocurrent values does not increase and if the shape of the % photocurrent spectrum does not alter (in particular the low-energy % photocurrent values should not increase) or if one or more of the % optical filters could not be used for an FTPS measurement, because % the signal-to-noise ratio in the interferogram was too low when % using that particular filter. if (samples_type_highest_filter == 0) highest_filter = samples_array{samples_counter,5}; elseif (samples_type_highest_filter == 1) highest_filter = samples_filter; elseif (samples_type_highest_filter == 2) highest_filter = number_FTIR_filters_used; end; if (use_OPTA == 0) % Define the name of the absolute absorption coefficient spectrum % to which the relative photocurrent spectrum is to be scaled. % For a film on glass, this name should be the same as the sample % name; for a solar cell, the RT measurement on the film % corresponding to the solar cell absorber layer should be % used. name_RT = samples_array{samples_counter,6};

% Define the directory where the RT measurement data are located. dir_RT = 'C:\mydocs\TU Delft\Jaar 5\Thesis\Jimmy\data\rt\nk\'; end;

% Adjust the maximum energy in eV up to which the data from the FTPS % measurement with a certain filter (RG645, RG695, FGL780, RG850, or % Si arc) is used if, after having set samples_type_highest_filter

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% equal to 1, it appears that the predefined maximum energies do not % result in a smooth spectrum at the connecting energies? Yes: 1, % No: 0. E_max_changed = 0;

%% ********************************************* %% %% *** PART 5/10: LOAD FTPS MEASUREMENT DATA *** %% %% ********************************************* %%

% Load the energy and absorption coefficient data obtained from the % RT measurement. if (use_OPTA == 0) [E_RT alpha_RT] = textread([dir_RT,name_RT,'.nk'],['%f %*f' ... ' %*f %f %*f %*f %*f'], ... 'delimiter',' ','headerlines',2); alpha_RT = abs(alpha_RT); end;

% Load FTPS measurement data of all used filters. data_FTPS_RG645 = csvread([dir_FTPS,name_sample,' rg645.csv']); if (highest_filter > 1) data_FTPS_RG695 = csvread([dir_FTPS,name_sample,' rg695.csv']); end; if (highest_filter > 2) data_FTPS_FGL780 = csvread([dir_FTPS,name_sample,' fgl780.csv']); end; if (highest_filter > 3) data_FTPS_RG850 = csvread([dir_FTPS,name_sample,' rg850.csv']); end; if (highest_filter > 4) data_FTPS_Si = csvread([dir_FTPS,name_sample,' si.csv']); end;

% Load background measurement data of all used filters measured by % the DTGS detector. data_background_RG645 = csvread([dir_background, ... 'background rg645.csv']); if (highest_filter > 1) data_background_RG695 = csvread([dir_background, ... 'background rg695.csv']); end; if (highest_filter > 2) data_background_FGL780 = csvread([dir_background, ... 'background fgl780.csv']); end; if (highest_filter > 3) data_background_RG850 = csvread([dir_background, ... 'background rg850.csv']); end; if (highest_filter > 4) data_background_Si = csvread([dir_background, ... 'background si.csv']);

140 end;

% Load the wavenumber and calculate the energy data from the FTPS % measurement data. wn_FTPS = data_FTPS_RG645(:,1); E_FTPS = wn_FTPS * nm_to_eV / 1e7;

%% ******************************************* %% %% *** PART 6/10: CORRECT LOADED FTPS DATA *** %% %% ******************************************* %%

% Correct the FTPS measurement data for the background measurement % data. alpha_FTPS_RG645 = data_FTPS_RG645(:,2) ./ data_background_RG645(:,2); if (highest_filter > 1) alpha_FTPS_RG695 = data_FTPS_RG695(:,2) ./ ... data_background_RG695(:,2); end; if (highest_filter > 2) alpha_FTPS_FGL780 = data_FTPS_FGL780(:,2) ./ ... data_background_FGL780(:,2); end; if (highest_filter > 3) alpha_FTPS_RG850 = data_FTPS_RG850(:,2) ./ ... data_background_RG850(:,2); end; if (highest_filter > 4) alpha_FTPS_Si = data_FTPS_Si(:,2) ./ data_background_Si(:,2); end;

% Correct the FTPS photocurrent data for the frequency dependence of % the DTGS detector by the wavenumber response at an FTIR mirror % velocity of 0.1581 cm/s. The correction polynomial is obtained from % background measurements with the DTGS detector measured at % different scanning velocities. After having calculated the % frequency response for each scanning velocity, normalisation of % these curves to the curve with the lowest wavenumber results in the % relative frequency response of the DTGS detector. The polynomial % used here is a fit of degree 5 through the data points of this % relative frequency response curve. p1 = -2.102e-023; p2 = 3.901e-018; p3 = -2.894e-013; p4 = 1.057e-008; p5 = -0.0001928; p6 = 1.536; corr = (p1 * wn_FTPS .^ 5) + (p2 * wn_FTPS .^ 4) + (p3 * wn_FTPS ... .^ 3) + (p4 * wn_FTPS .^ 2) + (p5 * wn_FTPS) + p6; alpha_FTPS_RG645 = alpha_FTPS_RG645 ./ corr; if (highest_filter > 1) alpha_FTPS_RG695 = alpha_FTPS_RG695 ./ corr; end;

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if (highest_filter > 2) alpha_FTPS_FGL780 = alpha_FTPS_FGL780 ./ corr; end; if (highest_filter > 3) alpha_FTPS_RG850 = alpha_FTPS_RG850 ./ corr; end; if (highest_filter > 4) alpha_FTPS_Si = alpha_FTPS_Si ./ corr; end;

% Correct the FTPS photocurrent data for the frequency dependence of % the a-Si detector (the sample under investigation) by the % wavenumber response at an FTIR spectrometer mirror velocity of % 0.1581 cm/s. The correction polynomial is obtained from FTPS % measurements on an a-Si:H film measured at different scanning % velocities. After having calculated the frequency response for each % scanning velocity, normalisation of these curves to the curve with % the lowest wavenumber results in the relative frequency response of % the a-Si detector. The polynomial used here is a fit of degree 5 % through the data points of this relative frequency response curve. p1 = -9.666e-021; p2 = 4.403e-016; p3 = -7.665e-012; p4 = 6.431e-008; p5 = -0.0002862; p6 = 1.453; corr = (p1 * wn_FTPS .^ 5) + (p2 * wn_FTPS .^ 4) + (p3 * wn_FTPS ... .^ 3) + (p4 * wn_FTPS .^ 2) + (p5 * wn_FTPS) + p6; alpha_FTPS_RG645 = alpha_FTPS_RG645 ./ corr; if (highest_filter > 1) alpha_FTPS_RG695 = alpha_FTPS_RG695 ./ corr; end; if (highest_filter > 2) alpha_FTPS_FGL780 = alpha_FTPS_FGL780 ./ corr; end; if (highest_filter > 3) alpha_FTPS_RG850 = alpha_FTPS_RG850 ./ corr; end; if (highest_filter > 4) alpha_FTPS_Si = alpha_FTPS_Si ./ corr; end; clear p1 p2 p3 p4 p5 p6 corr;

% Correct the FTPS photocurrent data for the energy dependence of the % DTGS detector in order to conserve the proportionality to the % number of photons hitting the detector. alpha_FTPS_RG645 = alpha_FTPS_RG645 ./ E_FTPS; if (highest_filter > 1) alpha_FTPS_RG695 = alpha_FTPS_RG695 ./ E_FTPS;

142 end; if (highest_filter > 2) alpha_FTPS_FGL780 = alpha_FTPS_FGL780 ./ E_FTPS; end; if (highest_filter > 3) alpha_FTPS_RG850 = alpha_FTPS_RG850 ./ E_FTPS; end; if (highest_filter > 4) alpha_FTPS_Si = alpha_FTPS_Si ./ E_FTPS; end;

%% ********************************************************* %% %% *** PART 7/10: SCALE CORRECTED FTPS PHOTOCURRENT DATA *** %% %% ********************************************************* %%

% Define the indices in the energy vectors up to which the data from % the FTPS measurement with a certain filter (RG645, RG695, FGL780, % RG850 or Si arc) are used. if (use_OPTA == 0) temp_index = find(E_RT >= E_max_RG645); start_index_RT = temp_index(1); end; temp_index = find(E_FTPS >= E_max_RG645); stop_index_RG645 = temp_index(1) - 1; if (highest_filter > 1) temp_index = find(E_FTPS >= E_max_RG695); stop_index_RG695 = temp_index(1) - 1; end; if (highest_filter > 2) temp_index = find(E_FTPS >= E_max_FGL780); stop_index_FGL780 = temp_index(1) - 1; end; if (highest_filter > 3) temp_index = find(E_FTPS >= E_max_RG850); stop_index_RG850 = temp_index(1) - 1; end; if (highest_filter > 4) temp_index = find(E_FTPS >= E_max_Si); stop_index_Si = temp_index(1) - 1; end; clear temp_index;

% Define the absorption coefficient from the RT measurement data to % which the relative photocurrent spectrum will be scaled. If this % scaling will not be performed in MATLAB, a dummy value is used for % scaling the relative photocurrent spectrum to the proper plotting % range. if (use_OPTA == 0) start_alpha_RT = alpha_RT(start_index_RT);

143 elseif (use_OPTA == 1) start_alpha_RT = 0.184036; % absorption coefficient at 1.85 eV % expressed in 1/um obtained from the % RT measurement of sample a2664 end;

% Calculate the scaling needed for the FTPS photocurrent data % obtained from measurements performed with each of the five optical % filters to create the relative photocurrent spectrum. scaling_RG645 = start_alpha_RT / (alpha_FTPS_RG645(stop_index_RG645)); if (highest_filter > 1) scaling_RG695 = scaling_RG645 * ... alpha_FTPS_RG645(stop_index_RG695) / ... alpha_FTPS_RG695(stop_index_RG695); end; if (highest_filter > 2) scaling_FGL780 = scaling_RG695 * ... alpha_FTPS_RG695(stop_index_FGL780) / ... alpha_FTPS_FGL780(stop_index_FGL780); end; if (highest_filter > 3) scaling_RG850 = scaling_FGL780 * ... alpha_FTPS_FGL780(stop_index_RG850) / ... alpha_FTPS_RG850(stop_index_RG850); end; if (highest_filter > 4) scaling_Si = scaling_RG850 * ... alpha_FTPS_RG850(stop_index_Si) / ... alpha_FTPS_Si(stop_index_Si); end;

% Perform the scaling needed for the photocurrent data obtained from % FTPS measurements with each of the optical filters to create the % relative photocurrent spectrum. alpha_FTPS_RG645 = alpha_FTPS_RG645 * scaling_RG645; if (highest_filter > 1) alpha_FTPS_RG695 = alpha_FTPS_RG695 * scaling_RG695; end; if (highest_filter > 2) alpha_FTPS_FGL780 = alpha_FTPS_FGL780 * scaling_FGL780; end; if (highest_filter > 3) alpha_FTPS_RG850 = alpha_FTPS_RG850 * scaling_RG850; end; if (highest_filter > 4) alpha_FTPS_Si = alpha_FTPS_Si * scaling_Si; end;

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%% ******************************************************** %% %% *** PART 8/10: CONNECT SCALED FTPS PHOTOCURRENT DATA *** %% %% ******************************************************** %%

% Construct the output energy vector. if (use_OPTA == 0) E_output(1:stop_index_RG645) = E_FTPS(1:stop_index_RG645); E_output(stop_index_RG645 + 1 : stop_index_RG645 + 1 + ... max(size(E_RT)) - start_index_RT) = ...

E_RT(start_index_RT:end); elseif (use_OPTA == 1) E_output = transpose(E_FTPS); end;

% Connect the photocurrent vectors of the FTPS measurements performed % with the different optical filters at the right energies to % construct the relative photocurrent vector. if (highest_filter > 4) alpha_output(1:stop_index_Si) = alpha_FTPS_Si(1:stop_index_Si); alpha_output(stop_index_Si + 1 : stop_index_RG850) = ... alpha_FTPS_RG850(stop_index_Si + 1 : stop_index_RG850); end; if (highest_filter == 4) alpha_output(1:stop_index_RG850) = ... alpha_FTPS_RG850(1:stop_index_RG850); end; if (highest_filter > 3) alpha_output(stop_index_RG850 + 1 : stop_index_FGL780) = ... alpha_FTPS_FGL780(stop_index_RG850 + 1 : stop_index_FGL780); end; if (highest_filter == 3) alpha_output(1:stop_index_FGL780) = ... alpha_FTPS_FGL780(1:stop_index_FGL780); end; if (highest_filter > 2) alpha_output(stop_index_FGL780 + 1 : stop_index_RG695) = ... alpha_FTPS_RG695(stop_index_FGL780 + 1 : stop_index_RG695); end; if (highest_filter == 2) alpha_output(1:stop_index_RG695) = ... alpha_FTPS_RG695(1:stop_index_RG695); end; if (use_OPTA == 0) if (highest_filter > 1) alpha_output(stop_index_RG695 + 1 : stop_index_RG645) = ... alpha_FTPS_RG645(stop_index_RG695 + 1 : stop_index_RG645); end;

if (highest_filter == 1) alpha_output(1:stop_index_RG645) = ... alpha_FTPS_RG645(1:stop_index_RG645);

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end;

alpha_output(stop_index_RG645 + 1 : stop_index_RG645 + 1 + ... max(size(E_RT)) - start_index_RT) = alpha_RT(start_index_RT:end); elseif (use_OPTA == 1) if (highest_filter > 1) alpha_output(stop_index_RG695 + 1 : ... max(size(alpha_FTPS_RG645))) = ... alpha_FTPS_RG645(stop_index_RG695 + 1 : end); end;

if (highest_filter == 1) alpha_output = transpose(alpha_FTPS_RG645); end; end;

%% ******************************************************** %% %% *** PART 9/10: MODIFY RELATIVE PHOTOCURRENT SPECTRUM *** %% %% *** FOR POST-PROCESSING *** %% %% ******************************************************** %%

% Reduce the number of data points in the energy and relative % absorption vectors by a factor of reduction_FTPS if % reduction_FTPS > 0. if (reduction_FTPS > 0) for i = 1:length(E_output); if (mod((i - 1),reduction_FTPS) == 0); E_temp((i - 1) / reduction_FTPS + 1) = E_output(i); alpha_temp((i - 1) / reduction_FTPS + 1) = ... alpha_output(i); end; end;

clear E_output alpha_output i; E_output = E_temp; alpha_output = alpha_temp; clear E_temp alpha_temp; end;

% Store the relative absorption values in 1/cm instead of % 1/um, the corresponding energy values in eV and the wavelength % values in nm; all in column vectors. alpha_output = transpose(abs(alpha_output * 1e4)); E_output = transpose(E_output); lambda_output = nm_to_eV ./ E_output;

%% ******************************************************** %% %% *** PART 10/10: PLOT AND STORE RELATIVE PHOTOCURRENT *** %% %% *** SPECTRUM *** %% %% ******************************************************** %%

% Plot the relative photocurrent spectrum. figure('NumberTitle','off','Name',name_sample) semilogy(E_output,alpha_output,colour_FTPS) xlabel('\bf{E (eV)}')

% Plot the FTPS / RT absorption coefficient spectrum without using % OPTA or removing the interference and store the plot in an *.emf

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% file (optional) and the spectral data in a comma-separated *.ftps % file. if (use_OPTA == 0) ylabel('\bf{\alpha (cm^{-1})}') axis([0.5 2.6 1e-7 1e6])

if (samples_type_highest_filter == 1) title(['\bf{FTPS / RT absorption spectrum} ',name_sample, ... ' (highest filter: ',num2str(highest_filter),')'], ... 'FontSize',11)

if (save_emf == 1) saveas(gcf,strcat(dir_output,name_sample,'_', ... num2str(highest_filter),'_MATLAB'),'emf') end;

else title(['\bf{FTPS / RT absorption spectrum} ', ... name_sample],'FontSize',11)

if (save_emf == 1) saveas(gcf,strcat(dir_output,name_sample,'_MATLAB') , ... 'emf') end; end;

output_FTPS = [E_output alpha_output];

if (samples_type_highest_filter == 1) dlmwrite([dir_output,name_sample,'_', , ... num2str(highest_filter),'_MATLAB.ftps'], ... output_FTPS);

else dlmwrite([dir_output,name_sample,'_MATLAB.ftps'], ... output_FTPS); end;

% Plot the relative photocurrent spectrum and store the plot in an % *.emf file (optional). Store the output wavelength, energy and % relative absorption values in an *.ftps.dbp file, using the same % syntax as is used in *.dbp files, so the relative photocurrent % spectrum can be loaded in OPTA to connect it to the absolute % absorption coefficient spectrum obtained from an RT measurement. elseif (use_OPTA == 1) ylabel('\bf{\alpha (a.u.)}') axis([0.5 1.934 1e-7 1e5])

if (samples_type_highest_filter == 1) title(['\bf{FTPS absorption spectrum} ',name_sample, ... ' (highest filter: ',num2str(highest_filter),')'], ... 'FontSize',11)

if (save_emf == 1) saveas(gcf,strcat(dir_output,name_sample,'_', ... num2str(highest_filter),'_relative'),'emf') end;

else

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title(['\bf{FTPS absorption spectrum} ',name_sample], ... 'FontSize',11)

if (save_emf == 1) saveas(gcf,strcat(dir_output,name_sample,'_relative'), ... 'emf') end; end;

dummy_output = ones(length(E_output),1); output_FTPS = [wrev(lambda_output) wrev(E_output) ... 63.950E-12 * dummy_output 0.024209 * ... dummy_output wrev(alpha_output) 12 * ... dummy_output 20.2 * dummy_output];

if (samples_type_highest_filter == 1) fid = fopen([dir_output,name_sample,'_', ... num2str(highest_filter), ... '_relative.ftps.dbp'],'w');

else fid = fopen([dir_output,name_sample, ... '_relative.ftps.dbp'],'w'); end;

fprintf(fid,'%s\n',['# ''L nm'' ''hv'' ', ... '''I amp'' ''V'' ''abs''', ... ' ''lamp V'' ''phase'' ']); precision = 5; fprintf(fid,['%12.5g %11.5g %11.3G %11.5g %11.', ... num2str(precision),'G %11.3f %11.3f\n'], ... output_FTPS'); fclose(fid); end; % End use_OPTA test. clear ans;

% Restore the original E_max values if they have been changed. if (E_max_changed == 1) E_max_RG645 = E_max_RG645_original; E_max_RG695 = E_max_RG695_original; E_max_FGL780 = E_max_FGL780_original; E_max_RG850 = E_max_RG850_original; E_max_Si = E_max_Si_original; end;

% End the while loop if samples_type_highest_filter ~=1. if (samples_type_highest_filter ~= 1) samples_filter = number_FTIR_filters_used + 1; else samples_filter = samples_filter + 1; end; end; % End samples_filter loop. end; % End samples_counter loop.

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