Silicon Based Hybrid Photonic Structures and Their Applications to Biosensing

SILICON BASED HYBRID PHOTONIC STRUCTURES AND THEIR APPLICATIONS TO BIOSENSING

by Hong Qiao

A thesis submitted in satisfaction of the requirements for the degree of Doctor of Philosophy In the faculty of Science

20 May, 2011

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‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

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Abstract

Porous silicon has been studied as an effective host, efficient emitter, sensor and recently, a candidate for photonic crystals. Convenient surface modification chemistry not only counteracts the drawbacks of surface instability that comes with nanostructured morphology, it also adds useful functionalities such as specific target capture for sensing utility. Structurally novel devices can also be realised through manipulating porous silicon multilayers. This thesis extends on the effort to explore the optical properties and applications of porous silicon through the construction of functional porous silicon structures assisted by surface chemistry. In addition, extraordinary optical properties resulting from peculiar behaviour of light in porous silicon multilayers as photonic crystals are investigated and exploited to broaden the understanding of structural novelty and practically, showing attractive prospects for biosensing applications.

Quantum dot doped porous silicon one dimensional microcavity structures have been fabricated by incorporating colloidal II-VI compound quantum dots into the microcavity assembled from two separately anodised Bragg mirrors. The formation of microcavity structures is facilitated by strong affinity between biomolecules. High quality microcavity structures built on quantum dots at 565 nm, 625 nm and 780 nm with this technique exhibit well defined stop bands and resonant modes with line-widths less than 3.5 nm. Enhancement of photoluminescence emission, spectral and spatial modification by the microcavities is observed. Tunable emission from the microcavities also suggests the potential applications in biosensing.

The outermost truncation of regular Bragg reflectors creates a new type of novel structure sustaining Bloch surface waves with promising capability for biosensing. The structure is passivated and functionalized using established surface chemistry. Biosensing capability of the structures is demonstrated by protease-catalytic cleavage reaction of grafted gelatin. A detection limit of 0.37 nM protease is obtained. The possibility of kinetics study is explored.

Fabrication and characterisation of high quality protein spaced porous silicon microcavities for sensing purposes are summarised. Gelatin is incorporated as the central layer of the microcavity structure and, as the sensing element in biosensing III

operation. Some constraints to the engendering protease sensing are identified and possible solutions to these problems, proposed.

Acknowledgements

I would like to present my deepest gratitude to my supervisor Professor Justin Gooding for his constant and timely support, guidance, and advices during the past three years. It is his encouragement, leniency and tactic motivation that consistently sustained my confidence on the journey towards the fulfilment of this thesis. His humour at leisure time, on the other hand, lessened my feeling of frustration and made tedious aspect of science less intimidating. He has been and will be my role model for his receptivity, integrity, impartiality, and seriousness about science.

I am indebted dearly to my co-supervisor Dr. Peter Reece with whom I spent most of my time on this tenuous and emotional journey. I have been strongly influenced by his wealthy knowledge, endless innovation and persistent optimism. It was Peter’s instructive and understandable tutoring in optics that walked me into an unfamiliar world striding chemistry and physics. His patience with my clumsiness in setting up experiment and data modelling helped muster up my courage to wade into the field of photonics, which has unexpectedly gripped my interest and held me for so long and so far. I wouldn’t have got where I am without his brilliant ideas at numerous critical points. Extra thanks also go to him for proof reading this thesis.

I am especially beholden to my compatriot Bin Guan, an enthusiastic and acquisitive fellow student equipped with superb surface chemistry skills. She is not only an independent hard worker, but also a helping hand which was available whenever I was in need. The success of the project is in part attributed to the unselfish assistance Bin provided.

I am grateful to Professor Mike Gal who witnessed my fumbling on the way of science in the past years. Being a respectable academic and an active role player in most collaborative projects with Biomaterials and Biosensors Research Group, he showcased me critical thinking and good practice in doing science by some insightful and inspiring discussions and questions.

Short accompany by Dr. Kristopher Kilian has proven to be crucially beneficial to the embarkment of my scientific pursuit. Big thanks go to Kris for ushering me into the nano-scaled realm of porous silicon which I found is grandiose in fact. Long after his leave from this group, he has been inspiring the porous silicon biosensor research not V

only with his benchmark work, but also by face-to face mentoring on spot and online discussion, which saved me a lot of detour and waste.

To Dr. Adam Micolich, Dr Jack Cochrane, Dorothy Yu, Rabia and Dr Kris Marjo, I would like to say thank you for your generosity to give me the permission to use all facilities in your sovereignty.

Heart-felted thanks also go to administration staff at school of chemistry: Mr Ken, Mr Rick, and let’s not forget you, Jodee.

Ignorance of my occasional invasion into Spectroscopy lab at school of chemistry by those in charge is also thankfully appreciated.

I would like to express my thanks to my colleague students: Muthu Chockalingam, Albert Ng, Alicia Gui, Will Rouesnel, Callie Fairman, Naomi Khor, Pauline Michaels, Simone Ciampi, Nadim Darwish, Josh Ginges and too many to mention. Your help, support discussion and particularly, persistent tolerance for so long, are well cherished here. Our friendship will go beyond nearly four years’ company.

UNSW, which gave me a taste of the academic life, deserves a good thank and memory of its vibrant campus atmosphere I was indulged in the past years.

However, the unconditional support and love from my family member: my wife Yanli Yang and my daughter Wenjing, should have been highlighted and appreciated in the first place. It was my family that provides me a warm, safe and comfortable nestle for me to build up energy and go forward. For all the guilt of negligence to my family which Wynne, my little princess of 14 months hasn’t even realised, may it be vindicated by the bits I have achieved in this thesis.

Table of Contents

ABSTRACT ...... II

ACKNOWLEDGEMENTS ...... IV

TABLE OF CONTENTS ...... VI

LIST OF FIGURES...... X

LIST OF TABLES ...... XIX

1 AN INTRODUCTION...... 1

1.1 POROUS SILICON: BACKGROUND ...... 1 1.2 POROUS SILICON FORMATION ...... 2 1.3 FROM PHOTOLUMINESCENCE TO PHOTONIC CRYSTALS ...... 6 1.3.1 LUMISCENT POROUS SILICON ...... 6 1.3.2 POROUSSILICON BASED PHOTONIC CRYSTALS ...... 7 1.3.2.1 PHOTONIC BAND GAP MATERIALS ...... 7 1.3.2.2 PHOTONIC CRYSTALS AS BIOSENSOR TRANSDUCERS ...... 10 1.3.2.3 MESOPOROUS MULTI THIN FILM PHOTONIC CRYSTALS ...... 10 1.3.3 POROUS SILICON FOR OPTOELECTRONIC UTILITY ...... 13 1.4 POROUS SILICON AS OPTICAL BIOSENSORS ...... 13 1.4.1 SENSING ON POROUS SILICON ...... 14 1.4.2 POROUS SILICON PHOTONIC CRYSTALS LABEL-FREE OPTICAL BIOSENSORS ...... 15 1.4.3 MOVING AWAY FROM MICROCAVITIES ...... 18 1.4.4 SURFACE CHEMISTRY: A KEY TO RELIABLE, FUNCTIONAL, SELECTIVE AND ROBUST SENSORS ...... 18 1.5 OTHER APPLICATIONS OF POROUS SILICON ...... 19 1.5.1 IN VIVO SENSORS ...... 19 1.5.2 DRUG DELIVERY ...... 19 1.5.3 CELL CULTIVATION AND TISSUE ENGINEERING ...... 19 1.6 SUMMARY AND OUTLINE OF THE THESIS ...... 20 REFERENCES ...... 22 2 EXPERIMENTAL SETUPS AND PROCEDURES ...... 32

2.1 MATERIALS AND REAGENTS ...... 32 2.2 FABRICATION OF POROUS SILICON ...... 34 2.2.1 ELECTROCHEMICAL ETCHING OF SILICON ...... 34 2.2.1.1 FABRICATION OF POROUS SILICON MICROCAVITIES ...... 36 2.2.1.2 FABRICATION OF BLOCH SURFACE WAVES SENSORS...... 37 2.2.2 MICROCAVITIES ASSEMBLED FROM FREE-STANDING POROUS SILICON ...... 38 2.3 SURFACE MODIFICATION AND FUNCTIONALISATION OF BLOCH SURFACE WAVES STRUCTURES ...... 39 2.3.1 HYDROSILYLATION OF POROUS SILICON ...... 40 2.3.2 FORMATION OF ANTI-FOULING MOLESULE LAYERS ...... 41 2.3.3 GELATIN IMMOBILISATION ...... 42 2.4 OPTICAL CHARACTERISATION OF POROUS SILICON ...... 42 VII

2.4.1 REFLECTIVITY ...... 42 2.4.1.1 NORMAL INCIDENT REFLECTIVITY MEASUREMENT ...... 42 2.4.1.2 SIMULATION OF MULTILAYERED POROUS SILICON ...... 43 2.4.1.2.1 EFFECTIVE MEDIUM APPROXIMATION (EMA) METHODS ...... 43 2.4.1.2.2 TRANSFER MATRIX METHODS (TMM) ...... 45 2.4.2 PHOTOLUMINESCENCE MEASUREMENT ...... 46 2.5 OPTICAL CHARACTERISATION OF POROUS SILICONSURFACE WAVE BIOSENSORS48 2.5.1 SPECTRAL REFLECTIVITY ...... 48 2.5.2 ENZYME TEST ON BSW SENSORS ...... 49 2.5.2.1 PROTEASE DETECTION ...... 49 2.5.2.2 ENZYMATIC KINETICS MONITORING ...... 49 REFERENCES ...... 50 3 OPTICAL PROPERTIES OF QUANTUM DOT DOPED POROUS SILICON MICROCAVITIES ...... 52

3.1 ACQUIRING LIGHT FROM SILICON ...... 52 3.2 LIGHT EMISSION FROM MICROCAVITY DEVICES ...... 54 3.2.1 CONTROL EMISSION WITH POROUS SILICON MICROCAVITIES ...... 55 3.2.2 INCORPORATING QUANTUM DOTS INTO MICROCAVITIES ...... 56 3.3 COLLOIDAL QUANTUM DOT DOPED POROUS SILICON MICROCAVITIES ...... 57 3.3.1 FABRICATION OF POROUS SILICON BRAGG REFLECTORS ...... 58 3.3.2 PRE-MODIFICATION OF BRAGG REFLECTORS ...... 59 3.3.3 ASSEMBLY OF HYBRID MICROCAVITY VIA BIOMOLECULAR AFFINITY ...... 61 3.4 OPTICAL PROPERTIES OF QUANTUM DOT DOPED POROUS SILICON MICROCAVITIES ...... 64 3.4.1 SPECULAR REFLECTIVITY MEASUREMENT ...... 64 3.4.2 PHOTOLUMINESCENCE ...... 65 3.4.2.1 ENHANCEMENT OF PHOTOLUMINESCENCE ...... 66 3.4.2.2 SPECTRAL NARROWNESS OF THE PL EMISSION ...... 70 3.4.2.3 SPATIAL CONCENTRATION OF THE PL EMISSION BY MICROCAVITIES ...... 73 3.4.3 TUNABLE EMISSION ON POROUS SILICON ...... 76 3.4.3.1 TUNING OF MICROCAVITY RESONANCES ...... 78 3.4.3.2 TUNING OF POROUS SILICON MICROCAVITIES ...... 78 3.4.3.3 IN SITU TUNING OF POROUS SILICON MICROCAVITIES ...... 79 3.4.3.4 TUNING POROUS SILICON MICROCAVITIES WITH EXTERNAL SUBSTANCES ...... 80 3.5 CONCLUSIONS AND FUTURE WORK ...... 82 REFERENCES ...... 85 4 BLOCH SURFACE WAVE BIOSENSORS BASED ON POROUS SILICON MULTILAYER STRUCTURES ...... 88 4.1 OPTICAL BIOSENSORS ...... 88 4.1.1 AN OVERVIEW ON BIOSENSORS ...... 88 4.1.2 OPTICAL BIOSENSORS ...... 90 4.2 LABEL-FREE OPTICAL BIOSENSORS ...... 92 4.2.1 EVANESCENT WAVE AS A SENSING PLATFORM...... 92 4.2.1.1 SURFACE PLASMON RESONANCE (SPR) BIOSENSORS ...... 93 4.2.1.2 EVANESCENT WAVES AT DIELECTRIC INTERFACES ...... 94 4.3 PHOTONIC CRYSTAL-BASED BIOSENSORS ...... 95 4.4 POROUS SILICON MULTILAYERS FOR BLOCH WAVE LOCALIZATION ...... 96 4.4.1 BLOCH WAVES IN 1-D PHOTONIC CRYSTALS ...... 96 4.4.2 SPATIAL OPTICAL CONFINEMENT ACROSS POROUS SILICON FOR BIOSENSING ...... 98 VIII

4.4.3 SURFACE WAVE BIOSENSORS ON POROUS SILICON ...... 100 4.5 SURFACE WAVES BIOSENSOR FABRICATION ...... 100 4.5.1 STRUCTURE DESIGN ...... 100 4.5.2 SENSOR FABRICATION ...... 101 4.6 CHARACTERISATION OF BSW STRUCTURE ...... 101 4.6.1 SPECTRAL REFLECTIVITY MEASUREMENT ...... 102 4.6.2 NUMERICAL MODELLING OF SURFACE MODE ...... 104 4.6.3 EFFECT OF TERMINAL LAYER THICKNESS ...... 106 4.6.4 EFFECT OF THE NUMBER OF PERIODS ...... 108 4.7 SURFACE CHEMISTRY FOR ROBUSTNESS, SPECIFICITY AND SELECTIVITY ...... 109 4.7.1 SURFACE PASSIVATION...... 109 4.7.2 HYDROSILYLATION AND ANTI-FOULING LAYER FORMATION ...... 110 4.7.3 SENSING ELEMENT IMMOBILISATION ...... 111 4.7.4 SENSOR RESPONSES ...... 112 4.8 CONCLUSION ...... 114 REFERENCES ...... 115 5 POROUS SILICON BLOCH SURFACE WAVE SENSORS FOR PROTEASE DETECTION ...... 120 5.1 PROTEASE IN LIVING SYSTEMS ...... 120 5.2 PROTEASE DETECTION TECHNIQUES ...... 122 5.2.1 ZYMOGRAPHY ...... 122 5.2.2 SPECTROSCOPIC TECHNIQUES FOR ENZYME ASSAYS ...... 122 5.2.2.1 FLUORESCENCE SPECTROSCOPY AND COLORIMETRY ...... 122 5.2.2.2 FÖRSTER RESONANCE ENERGY TRANSFER (FRET) ...... 123 5.2.3 SPECTROPHOTOMETRIC METHODS ...... 125 5.2.4 RADIOACTIVELY LABELLED SUBSTRATE FOR ENZYME ASSAYS...... 126 5.3 LABEL-FREE BIOSENSORS FOR ENZYME DETECTION ...... 126 5.4 PROTEASE ASSAYS USING POROUS SILICON BIOSENSORS ...... 127 5.4.1 IMMOBILISED ENZYME FOR SUBSTRATE DETECTION: ACTIVITY ASSAY ...... 127 5.4.2 PROTEASE DETECTION USING IMMOBILISED SUBSTRATE ...... 128 5.5 PROTEASE DETECTION ON POROUS SILICON BLOCH SURFACE WAVE BIOSENSORS . 130 5.5.1 SENSOR FABRICATION ...... 130 5.5.2 SURFACE MODIFICATION AND SUBSTRATE IMMOBILISATION ...... 131 5.5.3 PROTEASE DETECTION USING GELATIN MODIFIED BLOCH SURFACE WAVE BIOSENSORS ...... 133 5.5.4 KINETICS OBSERVATION ON BLOCH SURFACE WAVE BIOSENSORS ...... 140 5.5.4.1 SIMPLIFIED ENZYMATIC KINETICS: MICHAELIS-MENTEN EQUATION ...... 140 5.5.4.2 KINETIC MONITORING ON BSW BIOSENSOR SURFACE ...... 143 5.6 CONCLUSIONS AND PROSPECTS ...... 146 REFERENCES ...... 149 6 CONSTRUCTION AND CHARACTERISATION OF PROTEIN SPACED POROUS SILICON MICROCAVITY BIOSENSORS ...... 155 6.1 OPTICAL RESONATOR/MICROCAVITY BIOSENSORS...... 155 6.2 POROUS SILICON MICROCAVITIES AS LABEL-FREE BIOSENSORS ...... 157 6.3 FABRICATION OF HYBRID MICROCAVITY USING GELATIN AS THE SPACER ...... 158 6.3.1 DEVICE FABRICATION ...... 160 6.3.2 DESIGNED CAVITY PARAMETERS ...... 161 6.4 CHARACTERISATION OF GELATIN EMBEDDED MICROCAVITIES ...... 161 6.4.1 MEASUREMENT TECHNIQUES...... 161 IX

6.4.2 SPACER THICKNESS ...... 162 6.4.3 SPACER SURFACE ROUGHNESS ...... 163 6.5 ATTEMPTS TOWARDS PROTEASE DETECTION WITH GELATIN SPACED MICROCAVITIES ...... 165 6.5.1 SAMPLE ADMINISTRATION ...... 166 6.5.2 SPATIAL INCIDENCE OF PROBING LIGHT ...... 166 6.5.3 RESPONSE TO PROTEASE ...... 168 6.6 CONCLUSIONS AND FUTURE WORK ...... 170 REFERENCES ...... 172

7 GENERAL CONCLUSION ...... 175 7.1 SUMMARY ...... 175 7.2 OUTLOOK ...... 177 7.2.1 ...... 177 7.2.2 ...... 177

APPENDIX . LIST OF PUBLICATION ...... 178 A1 JOURNAL PUBLICATIONS ...... 178 A1 CONFERENCE PROCEEDINGS ...... 178

List of Figures

Figure 1.1 A typical i-V curve of p-type (upper graph) and n-type (bottom graph) silicon in hydrofluoric acid solution. Solid line denotes dark mode while dashed line denotes the response under illumination (figure adapted from ref [17])...... 2 Figure 1.2 Illustration of electrochemical in silicon. Holes drifting towards pore tips driven by the external electrical potential react with fluorine ions and facilitate the development of pores at the pore tips, leading to the formation of porous silicon...... 3 Figure 1.3 Natural photonic crystals and optical features. (a): Morpho butterfly66; (b): The spine of a sea mouse67; (c): Scanning electron micrograph of a butterfly (Vanessa kershawi) cornea ( Scale bar represents 2 μm)68; (d): Transmission electron micrograph of a quarter-wave stack with corrugations in the swimming crab Ovalipes moller (Scale bar represents 5 μm)69; (e): reflectivity spectra of beetle Hoplia coerulea scale (upper: measured, bottom: calculated at normal incidence (coloured) and an incident angle of 30˚)70...... 8 Figure 1.4 One dimensional photonic crystals and optical responses. a) SEM image of a microcavity created by a defect in an air hole array (1-D photonic crystal slab)80; b) transmission spectrum; c): schematic diagram of a Bragg reflection grating at normal incidence under the substrate82, 83. The structure consists of a low refractive index plastic material with a periodic surface structure that is coated with a thin layer of high refractive dielectric material; d): reflectivity spectrum of a GMR. Figures reprinted from ref [80] and [82] respectively ...... 9 Figure 1.5 Porous silicon multilayer structures and their optical presentation. Depending on the layer sequence and porosity modulation increment (continuous or discrete), reflectivity spectra are featured by a pronounced and sharp reflection peak for Rugate filter (a and d), a broad high reflection plateau (b and e), and a sharp transmission dip splitting the plateau for a microcavity (c and f)...... 12 Figure 1.6 An illustration of porous silicon microcavity biosensors. The top graph depicts a sensor based on red shift induced by introduction of foreign species into the sensor (increased effective refractive index) while the bottom graph demonstrates blue shift type sensors where signal is inflicted by displacement of materials in the sensor (reduced effective refractive index)...... 16 XI

Figure 2.1 a) Schematic diagram of electrochemical etching cell. b) Cross-sectional diagram of etching cell...... 34 Figure 2.2 Relation between porosity and etch rate and applied current on highly boron doped p+ silicon (orientation ‹100›, resistivity 1.5-2 mΩ.cm) in 25% hydrofluoric acid ethanolic solution as etchant at room temperature. Porosity increases steeply with current in low current range. Etch rate increases linearly with current...... 36 Figure 2.3 a) Illustrated sequence of a 6 period Bragg reflector. b) Illustrated layer arrangement of structure used for Bloch surface wave biosensors. c) and d) depict the current profiles used to generate the layer arrangements in a) and b), respectively. Short, high current pulses produces high porosity layer while low porosity layer is formed by long and low current durations...... 38 Figure 2.4 Normal incidence reflectivity measurement set up. White light is split and focused onto porous silicon sample surface in order to create a beam spot of approximately 50 μm to distinguish the inhomogeneity across the sample area. The setup is open for integration of photoluminescence measurement at normal and variable detection angles...... 43 Figure 2.5 Simulation of optical features in a porous silicon single layer (a), Bragg reflector (b) and (c) microcavity based on transfer matrix method...... 46 Figure 2.6 Schematic of experimental setup for photoluminescence measurement...... 47 Figure 2.7 Photoluminescence measurement setup using diode laser as probing light incorporated into normal incidence reflectivity set...... 47 Figure 2.8 Diagram of the Kretschmann-type prism coupling optical arrangement used for measuring the reflectivity of the surface wave sensor. The incident white light was polarized in the TE orientation and focused onto the prism using a 10 cm focal length lens. The reflected light is collected by a second lens and coupled to a spectrometer. . 48 Figure 3.1 Schematic illustration of hybrid microcavity fabricated by doping quantum dots between two porous silicon Bragg reflectors, both modified with biotinylated bovine serum albumin (biotin-BSA). One reflector (bottom mirror) is attached to the native silicon substrate while the top mirror is lifted off silicon substrate. Quantum dots streptavidin conjugates were immobilised on the bottom mirror through biological interaction between strptavidin and biotin which is attached to BSA. Central layer of the microcavity is constituted by two high porosity porous silicon layers where biotin-BSA is deposited...... 58 XII

Figure 3.2 Schematic illustration of quantum dot-streptavidin conjugate. Quantum dots are in core-shell structure composed of CdSe as the core and ZnS as the shell. The composition is capped by a protective layer of polymer on which streptavidin is grafted. Streptavidin has four sites for biotin molecule binding...... 60 Figure 3.3 Schematic illustration of quantum dots immobilisation via biomolecular interaction. Biotin-BSA is deposited on the high porosity layer of the bottom reflector, followed by quantum dot exposure. Biotin-BSA, having a molecular size of 14 ×4 ×4 nm3, is able to enter into high porosity layer with average pore size of approximately 20 nm but excluded by the low porosity layer. Biotin-BSA deposition and quantum dots immobilisation occur only in the high porosity layer...... 62 Figure 3.4 Cross-sectional scanning electron microscopy (SEM) image of a hybrid microcavity assembled from two Bragg reflectors. Distinct and smooth interfaces can be seen between layers and between two mirrors, indicative of effective bonding formed. Quantum dots are immobilised in high porosity layer and therefore at the very centre of the microcavity...... 63 Figure 3.5 Visual comparison between monolithically grown (a) and assembled microcavities (b) fabricated with the same etching parameters for the individual layers. Comparability of structures formed using two techniques are indicated by similar colours. Little ridges on the assembled structure were a result of imperfect assembly technique...... 63 Figure 3.6 Normal incidence reflectivity spectra of all-porous silicon and hybrid microcavity assembled from porous silicon Bragg reflectors...... 65 Figure 3.7 Influence of incubation time of quantum dot conjugate on PL emission intensity. PL measurement were made on quantum dot deposited Bragg reflector (bottom mirror), excited by 514.5 nm Ar+ laser. PL intensity increases with longer incubation time but excessive long incubation corroded the bottom mirror and failed the microcavity...... 67 Figure 3.8 Impact of surface chemistry on PL intensity of quantum dots on Bragg reflector. Freshly etched Bragg reflector (left panel) concentrated quantum dots and enhanced the peak intensity by 8 times whereas slightly oxidized surface (right panel) are more accessible to aqueous quantum dots suspension and therefore exhibited an enhancement of 28 times...... 68 Figure 3.9 Photoluminescence enhancement and dependence of output emission on pumping power. a) Photoluminescence of quantum dots modified by the PSi XIII

microcavity (red line) compared with that of quantum dots deposited on Bragg reflector with the same procedure. Photoluminescence emission at 627.5 nm was measured amplified by a factor of 8.2, while FWHM was narrowed to 6.5 nm from 30 nm. b) Dependence of output emission collected from microcavity on the excitation source input. Linear response across several orders of magnitude indicates fast radiative recombination time of quantum dots...... 69 Figure 3.10 a) Measured (black line) reflectivity spectrum of mesoporous silicon hybrid microcavity synthesized from two six-period Bragg reflectors with 800 nm quantum dots embedded in between and its simulation (red line). b) High resolution spectrum of the PL emission band (solid triangles) from quantum doped microcavity and Gaussian fit (solid line). c) Measured reflectivity spectrum (solid squares) around the cavity mode of 799.5 nm and Lorentz fit (solid line)...... 72 Figure 3.11 a) Measured reflectivity spectrum of microcavity assembled from low temperature etched Bragg reflectors, doped with quantum dots. b) Measured reflectivity (solid line) around the cavity mode and Lorentz fit (dotted line). FWHM of the cavity mode at 771.05 nm was measured as 1.37 nm...... 73 Figure 3.12 Directionality of microcavity modified PL emission. a) Schematic of PL angular dependence measurement setup. The focus lens and objective that collects the emitted light are mounted concentrically on a rotation stage equipped with a goniometer in regard to the beam spot on the sample surface. b) Measured angular dependent Pl emission spectra on increased collecting angle from normal to 28˚ with an increment of 4˚. The peak wavelength position shifts monotonically to the shorter wavelength, accompanied by peak broadening and intensity declining...... 74 Figure 3.13 Illustration of spatial radiation intensity distribution of a dipole position along the axis (z axis) of planar cavity of multiple λ mirror separation. Broadly distributed radiation pattern in free space becomes discrete and concentrated along the axis. Only λ/2 cavity gives one radiation pattern surrounding the cavity axis...... 75 Figure 3.14 Emission PWV evolution with collecting angle away from normal. A good agreement between measured (square) and predicted (solid line) using the model suggested by ref27 is obvious...... 76 Figure 3.15 Photoluminescenc spectra from quantum dot doped porous silicon microcavities designed for 565, 625, and 780 nm quantum dots, compared with the quantum dots deposited on a Bragg reflector. Similar modification of PL is observed on XIV

three microcavities. Higher peak intensity from 565 nm microcavity can be attributed to stronger absorption of the quantum dots in at the excitation wavelength (440 nm)...... 77 Figure 3.16 a) Reflectivity spectrum of microcavity designed for tuning of PL emission, centered at 663.5 nm. b) Emission spectra tuned by infiltrating water and 60% glycerol aqueous solution, respectively. The microcavity emission may be tuned across the wide emission band of 780 nm quantum dots...... 81 Figure 3.17 Tuning response of the quantum dot doped microcavity. PL PWV shift changes linearly with increased glycerol content in the mixture. Measured (hollow triangle) results are in agreement with modelled trend (solid line) by matrix transfer method...... 82 Figure 4.1 Schematic diagram of biosensors. Sensing events occur on the transducer surface interfaced with biorecognition elements of various types. Changes on transducer surface are the apparent stimuli that can be detected and converted into a readable signal by electronics system...... 89 Figure 4.2 Schematic diagram of label-free optical biosensors relying on measurement of bulk refractive index of the analyte solution by evanescent wave. Figure reprint from ref [5]...... 93 Figure 4.3 Diagrams of surface plasmon resonance sensors. a) SPR based on Krestchmann prism configuration6. Other light coupling geometries used for SPR excitation include planar waveguide (b)7 and optical fibre (c)8.. SPR can also be launched by multiple diffraction on low cost gratings (d)9are being used to overcome the drawback associated with bulky prism. Signal output of SPR can be resonance angle, resonance wavelength (d) or intensity (amplitude)...... 94 Figure 4.4 Illustrated field intensity profiles as a function of depth in a multilayer dielectric photonic crystal with an interface to air. The surface mode exists in the first layer. The graph reprinted from ref [33]...... 97 Figure 4.5 Field intensity profiles in a microcavity containing two multilayer Bragg reflectors (a) (adapted from ref [41]) and a structurally modified Bragg reflector (b) (adapted from ref [42]). In a microcavity, the field is confined around the central layer so the strongest field intensity is enclosed inside the structure and less accessible to the analyte. The field intensity reaches maximum in the last layer in a Bragg reflector if a defect is created in that layer...... 99 Figure 4.6 Reflectivity spectrum of a newly etched Bloch surface wave sensor. Surface mode appears at 632 nm with a FWHM of 15 nm, comparable with that of Rugate filters XV

but structure with open space is much simpler and friendlier to analyte capture as a sensor...... 103 Figure 4.7 Scanning electron microscopy images of a Bloch surface structure containing a 4 period Bragg reflector and an irregular layer. a) Top view image; b) cross sectional image. The irregular layer is at the bottom of the mirror. High porosity layer is in dark gray while low porosity layer is in light gray. Dotted scale bars give an indication of pore size and layer thicknesses...... 104 Figure 4.8 (a) experimentally measured (solid) and simulated (dotted) reflectivity spectrum for a freshly etched porous silicon optical Bloch surface wave sensor. Important features include the surface wave mode (631 nm), and the two band-edge modes (489 and 807 nm). (b) Refractive index profile of the surface wave structure at the surface wave mode coupling wavelength. The distance is measured relative to the interface between the prism and the multilayered film. Field intensity profiles for wavelengths corresponding to the band-edge modes and the surface wave mode are shown in (c) and (d), respectively...... 105 Figure 4.9 Dependence of spectral position of surface wave on the thickness (represented by etching time) of the top layer of porous silicon. Etching times for the bulk Bragg reflector are kept consistent for three samples. Mode line widths are 18, 18 and 17.5 nm, respectively while reflectivity dip becomes deeper towards longer wavelength...... 107 Figure 4.10 The effect of structural arrangement on Bloch surface mode. While regular Bragg reflector without a defect does not support surface mode, scattering and absorption loss of too many layers in the Bragg reflector overwhelm the surface mode even if a defect layer (S) exists...... 108 Figure 4.11 Dependence of Bloch surface modes in reflectivity spectra on the number of layer pairs in Bragg reflector. FWHM for structures having 3 (black line), 4 (red line), and 5 periods (green line) are 26 nm, 18 and 15 nm respectively...... 109 Figure 4.12 Spectral evolution of a Bloch surface wave structure during a hydrosilylation-NH2EO6 grafting surface modification process. Hydrosilylation and

NH2EO6 attachment reaction induced a red shift in Bloch mode of 19 nm and 17 nm respectively. As chemistry modifications occur in the whole structure, band edge shift caused by Bragg reflection in the bulk structure is noticeable (4 nm and 14 nm, respectively)...... 111 XVI

Figure 4.13 Optical shift after gelatin immobilisation. Because gelatin is mainly trapped in the top layer, the bulk Bragg reflector structure was not perturbed. This is reflected by only 1 nm red shift in band edge and a massive 37.5 nm red shift in surface mode.112 Figure 4.14 Responses of the BSW sensor to subtilisin and PBS, respectively. While protease exposure caused a blue shift of 8.5 nm, PBS treatment did not shift the surface mode, suggesting the cleavage of gelatin by protease. In both control and enzyme tests the band edge remains unchanged, indicating intact bulk mirror structure. The band edge can be used to monitor the non-specific events occurring in the bulk Bragg structure and therefore can potentially be a self-reference...... 113 Figure 5.1Schematic diagram of the QD-dye-peptide FRET-based sensor configuration. Dye-labeled peptides containing appropriate cleavage sites for protease are self- assembled onto the QD surface. FRET from the QD to the dye quenches the QD PL. FRET efficiency changes induced by proteolytic cleavage of the peptide reveal the amount of protease (activity). Figure adopted from ref [37]...... 124 Figure 5.2 (a) Schematic representation of chemical moieties grafted within mesoporous PSi: (1) hydrosilylation of undecylenic acid onto the Si-H surface (black), (2) activation and coupling of hexa(ethylene glycol) amine (red), (3) activation with DSC, and (4) immobilization of gelatin (green). (b) Schematic depiction of gelatin- loaded pores before (upper) and after proteolysis (bottom). The whole structure is impregnated with cleavage fragments that need to be discharged in order to achieve reduced effective refractive index. Figures are adopted from ref 58...... 129 Figure 5.3 Schematic structure of a short fragment of gelatin...... 132 Figure 5.4 Optical shift accompanying the step-wise surface modification processes. With the progress of surface chemistry, both the Bloch mode and band edge move to the longer wavelength. Note that gelatin immobilization only cause shift in the Bloch mode, indicating the exclusive bonding of gelatin in the very top layer...... 133 Figure 5.5 (a) Diagram of the porous silicon film mounted on the surface of the prism using a cover glass as a substrate and refractive index matching liquid. During the sensing experiments the biological suspension is applied to the top surface and permeates through the porous film. After a fixed period of time the solution is removed from the film and allowed to dry. (b) Illustration of gelatine cleavage on the sensor in discussion. As gelatin is majorly anchored in the top layer, proteolytic cleavage takes place in this layer accordingly. Cleavage products diffuse away quickly instead of going into small pores underneath...... 134 XVII

Figure 5.6 Experimentally measured reflectivity spectra of surface functionalized porous silicon optical surface wave sensor before and after exposure to 0.01mg/mL of enzyme in biological buffer. (a) A small shift after enzyme reaction as a result of adsorption of buffer salts residue and by-products of the enzymatic reaction that offsets the cleavage-induced response. (b) After water rinse, a large shift in the surface mode results whereas band edge returned to its original position...... 136 Figure 5.7 Optical shift of the Bloch mode after the sensor chips were exposed to 0.0001 mg/ml (3.7 nM) subtilisin (a) and PBS Silane buffer solution for 90 min. unchanged mode widths on both occasions indicate the robustness of the sensor and homogeneous cleavage...... 138 Figure 5.8 Dependence of average velocity of the Bloch mode shift on the concentration of protease. Linear relationship indicates that at all concentrations studied, gelatin cleavage is controlled by protease catalysis. The linearity is the basis of protease quantification. Error bars are standard deviation based on replicate runs of at least 4...... 139 Figure 5.9 a) Depiction of different stages enzymatic reaction; the steady state region (labeled) occurs where no significant substrate consumption or production accumulation and ES complex remains constant concentration. b) Initial rates exhibit varied dependence on input substrate concentrations. c) Time courses (reaction progress curves) of reactions at different levels of enzyme. r1-r4 are initial velocities of reactions, obtained by linear fitting of the initial stages of the reactions, corresponding to variable enzyme concentrations ([E]1-[E]4.). Initial velocities and kinetic characterization can all be obtained from progress curve fitting...... 141 Figure 5.10 Kinetic constant estimation via discontinuous monitoring of the reaction and fitting the data to the rate equation. Consistent values obtained in reaction at different protease levels reveal similar reaction mechanism for all protease concentrations...... 145 Figure 5.11 Dynamic monitoring on protease (0.003mg/ml, red solid dots), PBS control (hollow squares) and deactivated protease (0.005 mg/ml, denaturized, hollow diamonds)...... 146 Figure 5.12 The predicted spectral response of the optical Bloch surface mode and Band-edge mode to changes in the relative fraction of gelatin filling the pore space of the porous silicon layers: (a) changes occurring only in the top layer, and (b), changes XVIII

occurring uniformly through the entire structure. The corresponding change in refractive index is displayed on the top axis...... 148 Figure 6.1 Schematic of Fabry-Perot cavity formed by two reflectors (top). The bottom is a reflectivity spectrum indicating the dependence of resonance wavelength on the cavity separation...... 156 Figure 6.2 Illustration of the gelatin spaced microcavity fabrication process...... 160 Figure 6.3 Left: scanning electron microscopic image of porous silicon microcavity with a gelatin layer embedded between two identical 6 period Bragg mirrors. Right: reflectivity spectrum of the Bragg mirror (black line) and the microcavity (red line). The microcavity has a resonance dip at 825.5 nm and a line width of 5 nm, corresponding to a Q-factor of 165.1...... 161 Figure 6.4 a): Reflectivity spectra exhibiting resonance wavelength values taken at different position (indicated in the inset) on one sample; b): values and variation of resonance wavelength (blue line and the calculated thickness (red line) from 9 readouts; c): average thicknesses of 9 replicate microcavities calculated as in a). Error bars represent standard deviation of at least 5 measurements...... 163 Figure 6.5 Atomic force microscopic images of gelatin layer spun on a porous silicon Bragg mirror indicating the mean roughness of the spun surface...... 164 Figure 6.6 Comparison of sample administration pathways between the monolithic (left) and the hybrid (right) microcavities...... 166 Figure 6.7 Two typical ways sample solution is delivered. While it is hard to avoid the disruption of signal reading due to the interference from liquid membrane in the horizontal configuration (left), vertical configuration (right) hardly yields responses due to the hydraulic restriction...... 167 Figure 6.8 Optical responses obtained from silicon-supported (left) and glass-supported microcavities. Independent optical interrogation space rules out the signal disruption caused by scattering at sample solution surface...... 168 Figure 6.9 optical responses of a microcavity structure to 0.1 mg/ml subtilisin and PBS buffer respectively. Red shifts in are attributed to swelling of gelatin, accumulation and retention of cleavage debris...... 169 Figure 6.10 Envisaged microcavity structure with improved surface stability, antifouling capability and mechanical integrity, resulting from surface modification and functionalisation...... 172

XIX

List of tables

Table 2.1 Chemicals, reagents and materials used in this research...... 32 Table 2.2 Expected porosities of component high and low porosity layers and applied etching conditions (current and etching time)...... 37 Table 2.3 Typical EMA numerical models used for porous material characterisation .. 44 Table 5.1 Initial rates, represented by shift rates of surface mode under the catalysis of subtilisin, corresponding to subtilisin input concentration...... 138

Chapter 1

An introduction

In this chapter a brief summary of the history, formation and current research activities of porous silicon as a nanostructured material is presented. Specifically, this chapter will focus on the structurally dependent optical properties of porous silicon multilayer structures and their applications for one-dimensional photonic crystal and subsequently as a candidate for biosensor transducer.

1.1 Porous silicon: background

Porous silicon (PSi) was discovered in Bell Lab1, 2 as an unexpected by-product of electrochemical polishing of silicon over a half century ago. For a long time, porous silicon was employed in microelectronic industry as nothing more than an insulating medium for silicon3, 4. It had not been given proper attention until the discovery of bright photoluminescence in highly porous architecture formed electrochemically in 19845. Successful observation of room temperature photoluminescence on porous silicon by Canham6 and Lehmann7 in 1990s marked a milestone and strong interest in porous silicon research ensued. Highly porous silicon, as well as silicon quantum dots (nanocrystals), emit light in the red, orange, yellow, green and blue regions when excited with light of higher energy. These light emitting properties of porous silicon have since been extensively investigated8-11. The pursuit for the drive of light emitting properties of porous silicon eventually led to the acceptance that, like other low dimensional materials, dramatic change in optical, electronic and mechanic properties arise as a result of reduced structural size of crystalline silicon to nanometric7, along with other completely new properties being observed. Furthermore, compatible fabrication and assembly techniques of porous silicon may imply a conceivable possibility of optical interconnects and optical-electronic integrated circuits (OEIC) based on miniaturised devices built up from silicon12, 13. In the meantime, engineering of morphology of porous silicon has seen expansive applications ranging from host materials14, light emitters15 to biosensors16 and drug delivery vehicles17, 18.

1.2 Porous silicon formation

Since the discovery of porous silicon during electrochemical polishing, electrochemical etching has been the dominant technique to create porous silicon; though other 19-21 approaches, such as stain etch using HF/HNO3, have been reported . The understanding of the electrochemical dissolution of silicon is primarily based on the i-V relationship at the silicon–electrolyte interface. i-V curves of the electrochemical process on p-type and n-type silicon to form porous silicon shown in figure 1.122 give a demonstration of electrochemical conditions for porous silicon formation.

As a matter of fact, the chemical process proceeds so slowly that unless driven by an external force, it is negligible. To realise etching, an electrical field is exerted where silicon has to be anodic biased. Therefore the electrochemical dissolution process of

silicon is also referred to as anodization. A typical setup used for porous silicon formation by anodic dissolution of crystalline silicon in hydrofluoric acid based medium is illustrated in Figure 1.2.

Figure 1.2 Illustration of electrochemical dissolution in silicon. Holes drifting towards pore tips driven by the external electrical potential react with fluorine ions and facilitate the development of pores at the pore tips, leading to the formation of porous silicon.

Electrochemical etching is usually conducted in galvanostatic mode (constant currents under varied potentials), at the current densities below polishing threshold prescribed in figure 1.1. The reaction scheme of the silicon dissolution is universally accepted as a 23 reaction involving formation of H2SiF6 :

+ - Si+6HF→H2SiF6 +H2+2H +2e

A more plausible and holistic understanding of electrochemical reaction of silicon in HF is that depending on the concentration of HF, and current density, applied in the electrochemical dissolution, silicon display a valence from 2 to 4, involving a varied number of holes and leading to formation of multiple species including SiO2 and SiO4. The exact mechanism behind anodization is still subject to debate, despite highly complex and reproducible fabrications of porous silicon being practicable24-27. Among numerous explanations proposed, a well accepted mechanism is quantum confinement28 which postulates that the anodization process is controlled by the supply of holes, which is more abundant at the etching front. Due to carrier confinement inflicted by an expanded band gap in low dimension pore walls, etching turns out to be a self- controlled process, with new dissolution focused at the pore tips while pore wall expansion is prohibited due to hole depletion29. Such a self-limited etching process leads to the creation of layered dielectric structures on silicon. As will be mentioned in proceeding sections, quantum confinement is also recognised as the model that governs the photoluminescence of porous silicon.

The current at the interface of Si-electrolyte is carried by holes (positively charged ions from silicon) which are provided by doping impurities in silicon wafers30, 31. Therefore, electrochemical etching on p+-type (highly boron doped) silicon is a straightforward process as it has higher population of carriers. By contrast, as is shown in Figure 1.1, n- type silicon will not undergo effective electrochemical dissolution in the dark even under high voltage, hence, with most n-type silicon, assistance is required by means of illumination such as UV or visible light32-34. The morphology (surface roughness of pore walls, orientation of pores, branch and interconnection of pores) of porous silicon is mainly determined by the dopant type and concentration in silicon, and to a lesser extent by etching parameters such as electrolyte composition, current density and illumination35, 36. It has been found that p-type silicon produces small pores and inter- pore spacing and large specific surface area (total surface area per unit mass or volume of material, m2/g or m2/cm3)37, 38. Porous silicon grown on low doped p-type silicon (resistivity >1 Ω cm) may have porosity of 40-60% and pore sizes of 2 nm; medium doped p-type silicon (0.001-0.1 Ω cm) tends to generate interconnected network with porosity of 30-80% and pore sizes of below 10 nm. Highly doped silicon (<0.01 Ω Cm)

produces pores of 10-100 nm with fewer branches and smoother interfaces. n-type silicon, on the other hand, tends to yield large pores (10-100 nm) with regular outline.

The solution chemistry plays an important role in pore formation39. In practice, in order to obtain smooth layer-to-layer interfaces and limit branch development, porous silicon formation by electrochemical etching is often carried out in solution containing surfactants such as ethanol. Inclusion of ethanol in electrolyte reduces the surface tension of the solution, thus improving penetration of electrolyte into the pores and 40 assists discharge of hydrogen bubbles produced in anodization . H2 bubbles generated at the Si-electrolyte interface tend to block the contact between HF and silicon, diverting away current flow from pore growth direction and leading to side pore 41 growth . With the progress of etching, it gets harder for H2 to diffuse away from the interface thus inhomogeneity emerges along the longitudinal direction of pore growth as a result. To mitigate the in-depth inhomogeneity and facilitate electrolyte regeneration, a number of current breaks are introduced into the etching current profile. Etching at low temperature helps reduce interface roughness and improves controllability over pore morphology42, 43 .

There are three categories of porous materials, classified by the International Union of Pure and Applied Chemistry (IUPAC)37 nomenclature based on the pore sizes: micropores (<10 nm), mesopores (10-50 nm), and macropores (50-200 nm). However, this classification only considers the average pore diameters and is more or less ambiguous. A more realistic classification has been proposed which takes pore morphologies, such as orientation, into account44.

Porosity, the ratio of the voids to the total volume of the structure for a given set of creation conditions, is proportional to the current density applied. Etch rate, another important parameter governing the properties of porous silicon, is proportional to current density but decreases with increased electrolyte concentration. The dependence of porosity and etching rate of p-type silicon on etching conditions will be discussed in detail in chapter 2. The control of the porosity and the thickness of individual layers in porous silicon preparation led to the advent of multilayered porous silicon structures45-47. Pore growth turns out to be a self-limiting process and pore growth proceeds towards 5

the source of holes at a uniform velocity across the whole area under etching. Therefore, under fixed etching conditions, such as electrolyte concentration, crystallographic orientation, dopant level and temperature, a uniform porous silicon layer of well defined porosity and thickness can be formed by applying a constant current pulse for a given period of time. When a current pulse is terminated, pore growth stops. Etching resumes when another pulse of current is applied. The subsequent development of the pores corresponds to the value of newly imposed current density and pore growth occurs only at the pore tips, hence a distinct interface will be shaped out. For a certain silicon substrate and HF concentration, by simply applying a predesigned in-depth current profile, porous silicon can be formed in a layer by layer style to a very large number of layers in any arbitrary sequence on one substrate48-51. A single layer is generated by applying one constant current or multiple consecutive identical pulses, depending on the thickness required, whereas alternatively applied high and low current densities gives rise to stacks containing periodic low and high porosity layers. Judicious choice of silicon substrate and careful control of etching parameters can lead to anything from optically flat single layer to ensembles containing hundreds of individual layers with high quality.

Mesoporous silicon with pore size of 10-50 nm and less branched pores, has smoother layer-to-layer interfaces and thus less incoherent scattering of light52. Compared with its microporous counterpart which features smaller nanopores and more susceptible to oxidation induced ageing, mesoporous silicon allows larger porosity modulation and is suitable for photonic material applications53, 54. In spite of the low luminescence efficiency, mesoporous silicon can be a substitute for microporous silicon since it is mechanically stable. For applications such as biosensing, mesopores are a logical consideration due to comparability of their size with biomolecules and therefore, will be the target of this thesis.

1.3 From photoluminescence to photonic crystals

1.3.1 Luminescent porous silicon

Porous silicon first attracted considerable attention almost two decades after the discovery of its efficient room temperature photoluminescence (PL) in 1990, although

bright photoluminescence was first observed at low temperature by Pickering et al in 19845.

The exact origin of the photoluminescence (PL) of PSi is still under debate, although some models have been proposed to describe the intricate luminescence phenomena. Some plausible mechanisms attributed the luminescent nature of porous silicon to structural or compositional changes incurred in the PSi formation process. It was demonstrated that such as surface states, defects, chemical species (polysilane, siloxene chains), and hydrogenated amorphous silicon on porous silicon surface can play a role in luminescing55. Subsequent work by Canham56, Lehmann8 and other authors57, 58 revealed that photoluminescence from porous silicon is related to the quantum confinement as a consequence of dimension reduction which leads to the widening of the band gap of silicon. Quantum confinement effect governed by the crystalline size of porous silicon was also observed by other authors59, 60. However, the quantum confinement theory is not consistently supported by experimental results61.

1.3.2 Porous silicon based photonic Crystals

1.3.2.1 Photonic band gap materials

Photonic crystals stemmed from the idea proposed by Yablonovitch62 and John63 to design materials that can affect the behaviour of photons in the similar way semiconductor crystals do to electrons. While both papers suggested the influence on the nature of photonic modes in materials with periodic variation of dielectric constant, the former aimed to address the loss experienced in the effort to use metallic reflectors in control over spontaneous emission whereas the latter emphasized the photon localisation effect by introducing a random variation into refractive index periodicity. As a matter of fact, there is a great abundance of photonic crystals in nature, ranging from prevalent 1-dimensional photonic crystals found in some insect wings, to 3- dimensional photonic crystals such as animal scales, skins, shells64 and gem opals65. Natural photonic crystals are used for signalling, camouflage or even thermoregulation by some insects and crustaceans. Some examples of natural photonic crystals are shown in Figure 1.3.

Figure 1.3 Natural photonic crystals and optical features. (a): Morpho butterfly66; (b): The spine of a sea mouse67; (c): Scanning electron micrograph of a butterfly (Vanessa kershawi) cornea ( Scale bar represents 2 μm)68; (d): Transmission electron micrograph of a quarter-wave stack with corrugations in the swimming crab Ovalipes moller (Scale bar represents 5 μm)69; (e): reflectivity spectra of beetle Hoplia coerulea scale (upper: measured, bottom: calculated at normal incidence (coloured) and an incident angle of 30˚)70.

In a broader sense, photonic crystals, or photonic band gap materials, are those structures featured by spatial dependence of refractive index and high refractive index contrast between elements at the scale of the wavelength of light. Regular periodicity and high contrast of refractive indices between components exert a strong influence on the radiation, transport and interaction of light. Analogous with crystals where electrons travel, spatially periodic variation of refractive index defines a vacuum frequency region or photonic gap where emission and propagation are forbidden. Periodic modulation of refractive indices can be arranged in such a way that 1, 2, and 3 dimensional photonic crystals can result. Moreover, by introducing defects, a resonator is formed where localisation of light is possible. Photonic crystals offer a completely new mechanism by

which to manipulate light spectrally, spatially and temporally instead of relying on total internal reflection which is limited by difficulties in fabrication and miniaturisation71.

Although there are reports of success72-74, synthesis of 3-D photonic crystals in near infrared region is so far extremely difficult because current micro- and nano-fabrication techniques have difficulties in achieving spatial modulation of refractive index in the magnitude of nanometres in multiple dimensions. The literature on 2-D photonic crystals is increasing rapidly due to the relative ease of fabrication75-77. In fact, before the introduction of the concept of photonic crystals, 1-D photonic devices such as Bragg reflectors and dielectric mirrors were actively used since as early as 1950s78. Following the studies on optical waves in layered media in 1970s79, multilayer thin films or Fabry- Perot filters have become the most investigated one dimensional 1-D photonic structures, as we will discuss in chapter 3. Some other formats of 1-D photonic crystals such as air hole arrays80, or Bragg reflection gratings or guided-mode resonant (GMR) system81, are shown in Figure 1.4 (c).

Figure 1.4 One dimensional photonic crystals and optical responses. a) SEM image of a microcavity created by a defect in an air hole array (1-D photonic crystal slab)80; b) transmission 9

spectrum; c): schematic diagram of a Bragg reflection grating at normal incidence under the substrate82, 83. The structure consists of a low refractive index plastic material with a periodic surface structure that is coated with a thin layer of high refractive dielectric material; d): reflectivity spectrum of a GMR. Figures reprinted from ref [80] and [82] respectively.

A diverse range of growth techniques are available for fabricating 1-D photonic crystals, including self-assembly84, 85, sol-gel technique86, chemical vapour deposition87, sputtering88, molecular beam epitaxy89 or their combination90. Top-down fabrication schemes for 1-D photonic crystal slabs and gratings utilise direct-write (e.g. laser ablation), or lithographic technologies, such as electron beam lithography and reactive ion etching91. Typically there is a trade-off between the optical quality of the photonic crystals and the complexity and cost-effectiveness of the fabrication method used to produce them. There is a high demand for straightforward and cost-effective techniques for device implementation based on 1-D photonic crystals. This has been exemplified by the multilayer thin film structures and their derivatives obtained92 from silicon.

1.3.2.2 Photonic crystals as the optical biosensor transducers

Photonic crystals have been employed as optical sensing transducers thanks to their capability of effective light manipulation and sensitive response to the presence of target analytes which change the optical properties of the photonic crystals. Sensing can be accomplished in a label-free, reagent free, non-contact through distant observation of colorimetric changes on the photonic crystals. Apart from fast response and fidelity of the optical signal characteristic of most optical sensors, natural compatibility of sensor material with integrated circuits is becoming an important feature of merit for miniaturised photonic crystal devices which hold the hope for multiplexed and integrated sensing system93.

1.3.2.3 Mesoporous multi thin film photonic crystals

The possibility of mesoporous composites for photonic utility is enabled by the correlation between optical and dielectric constants (refractive index) and the volumetric ratio of void in the porous medium, known as porosity. In a multilayered porous matrix, silicon clusters of the host material and the void occupied by air are in sizes far smaller than the wavelength of light which cannot resolve the size variation on

this scale. On the scale of optical wavelengths, these heterogeneous media look homogeneous (isotropic) and light propagates in the quasi-homogeneous media with minimal internal scattering. However, at the interface between two porous phases of differing composition, light will experience strong Fresnel reflection due to the sharp step in dielectric properties. Periodically arranged layers of porous regions with dimensions comparable to light wavelength, exerts strong scattering on light as a result of Bragg reflection (coherent scattering). Refractive index of such a heterogeneous nanocomposite can be predicted with various Effective Medium Approximation Methods which treat a layer of porous matrix as a mixed dielectric. In the next chapter, a number of approximation models used for refractive index estimation on porous silicon will be discussed.

Mesoporous multilayer structures aimed for use as photonic crystals have been demonstrated in various materials such as semiconductors (II-VI, III-V)94, 95, oxides96-98, ceramics and silicon99. As has been pointed out in the previous section (1.2), the porosity of a porous silicon multilayer stack can be harnessed from 20% to 90% in a tuneable fashion, corresponding to an effective refractive index variation of up to 1.8 between neighbouring layers, it is an ideal candidate to be considered as a photonic crystal. Porous silicon based 2 and 3 dimensional photonic crystals have been reported100-102.

Figure 1.5 Porous silicon multilayer structures and their corresponding optical spectra. Depending on the layer sequence and porosity modulation increment (continuous or discrete), reflectivity spectra are featured by a pronounced and sharp reflection peak for Rugate filter (a and d), a broad, high reflection plateau (b and e), and a sharp transmission dip splitting the plateau for a microcavity (c and f).

Figure 1.5 shows major multilayered structures fabricated on mesoporous silicon. λ/4 Distributed Bragg reflectors (Figure 1.3d and e) with alternating multilayer sequence of

(LH) n (L: low porosity layer; H; High porosity layer; n: the number of alternative layer pairs) with a wide high reflection plateau and 1-D microcavities (Figure 1.32 and f) derived from Bragg reflectors will make the core theme of this study. A microcavity is featured by a central layer of multiple λ/2, flanked by two Bragg reflectors. Compared with Bragg reflector, a microcavity has a sharp optical dip pronounced in the wide reflection plateau of the Bragg reflector. The performance of a microcavity is typically interpreted by a Q factor, expressed as the ratio of the resonance wavelength to the full width at half maximum (FWHM) of the cavity, i.e. λo/∆λ. A microcavity with a high Q factor which indicates the high extent of field confinement in the cavity offers higher potential sensitivity to stimuli in sensing applications. Q factor is determined by the number of component layer pairs and the refractive index contrast between neighbouring layers. FWHM of 0.21 nm and a Q-factor of up to 7300 have been

achieved on porous silicon microcavity by Reece et al103. Porous silicon based Rugate filters (Figure 1.3a and d) with nearly continuous modulation of porosity and therefore refractive index have been realised by dynamic control over the etching parameters50, 104, 105. Compared with other multilayer deposition techniques restrained by difficulties in switching between different stoichiometries during deposition, Rugate filters fabrication on porous silicon holds substantial advantage. 1.3.3 Porous silicon for optoelectronic utility

Optical and photonic devices based on porous silicon have been a major goal in overcoming the intrinsic luminescence inefficiency of silicon since the discovery of its photoluminescence. Besides being an efficient light emitter, controllability and tunability of pore morphology, coupled with multilayer capability, porous silicon open up the door to the development of a multitude of applications in optics and optoelectronics such as mirrors106-108, filters109, 110, light emitting diodes92, 111, photodetectors112, 113, waveguides114, microcavities115, 116, switching and modulators117. Massive specific area (up to 900 m2 /cm3) and high reactivity of porous silicon leave huge space for surface engineering added extra functionalities to this material and make it an ideal host material to accommodate active media for device implementation through doping and impregnation118, 119.

Despite the successful demonstration for multiple applications, monolithic porous silicon structures of all porous silicon fail to provide flexibility in device construction. One of the goals of this study is to take advantage of flexible fabrication techniques of porous silicon multilayers to build efficient and cost effective light emitting devices by incorporation of active media such as quantum dots into a microcavity. What the author will try to achieve in this work is assembling so-called hybrid microcavities with porous silicon Bragg reflector building blocks via natural affinity between biomolecules.

1.4 Porous silicon as optical biosensors

Generally, optical biosensors are realized based on the fact that biomolecules have the capability to reduce the propagation velocity of light that interact with them. A number of optical properties are being used in sensing. Absorption based sensor is established on the fact that the absorbance is proportional to the amount of absorbing material

present. Substances that can absorb light at specific wavelengths can be detected as the absorbance. Or alternatively, an absorbing indicator that binds to the target material and changes the absorbance can be used to detect the substance of interest indirectly. Sensing can also be implemented by measuring the changes of local refractive index by biorecognition events. Binding events at the sensor surface lead to a change in refractive index of the medium in the vicinity of the sensor surface, causing an appreciable shift in the spectral features of the light passing through the sensor surface. A typical example of this type of biosensors is Surface Plasmon resonance that detects the changes in refractive index caused by the binding of target materials. Dissipation of plasmon modes to the surrounding environment including biomolecules produces a dip in the spectrum of reflected light. Binding activities at the interface are represented by a shift in light coupling conditions (angle) or frequency (wavelength). Resonant microcavityˈ as will be discussed in the following chapters, is another example of refractive index based sensing vehicle. In a microcavity, resonant conditions are determined by both refractive index and the separation of the cavity. A change in either refractive index or cavity size, initiated by the binding events of biomolecules to their complementary, would change the resonance conditions and be detected as a shift the spectral features.

Q factor is a measure of light confinement in a cavity., A higher Q-factor indicates a cavity should be high enough to allow the wavelength shift caused by the refractive index (RI) change to be resolved.

1.4.1 Sensing on porous silicon

From the very beginning of the exploration into porous silicon, there emerged two major fields of effort: optical materials for optoelectronics and transducer for biosensing. Porous silicon is an ideal material for use as a biosensing transducer. As a result of the large available surface area and photonic structure generated in anodic etching, it not only has the capacity to accommodate large amount of chemicals as the receptors for specific and selective capture, but also offers the capability to sensitively translate chemical or biological molecular events into legible readouts without using any reagents. Compatibility with microelectronic processing and electronic integration techniques present the possibility of integrated smart sensors or so-called lab-on-a-chip120-122. In the last decades, activities in sensing study that take advantage of these unique properties of 14

porous silicon have been very extensive. There are two major sensing modes which use porous silicon as optical transducer. Early works capitalized on efficient photoluminescence given off by porous silicon. In this mode, photoluminescence of porous silicon is quenched by target analyte ingress123, 124. The extent of quenching is translated into the amount of analytes present in the porous silicon network. The intrinsic photoluminescence band of porous silicon is broad and susceptible to interferences from unpredictable and uncontrollable factors125-127, as a result, photoluminescence measurements are hard to interpret and far from reliable. Like other semiconductors, porous silicon is usually characterised with spectral reflectivity measurement by shining white light and observing reflection, transmission or diffraction. Interferometry is another mode that takes advantage of the optical features arising from interference of the reflected light at the interfaces of multilayer structures. Porous silicon interferometric biosensing application was firstly demonstrated by Lin et al128 where protein (streptavidin and antibody) interactions with their ligands were monitored as spectral shifts in reflection of visible light on a single porous silicon film. A huge 129 130 131 132-134 range of sensing targets from humidity , HF , NOx , organic gases , solvents135, pesticides136, 137, to bacteria138, 139, viruses140, 141, DNA142, drugs143, 144 and explosives124 have since been reported. Step-wise synthesis of peptide capitalising on the massive surface, facile coupling chemistry, and intrinsic detection capability of porous silicon was monitored in real-time by Delouise and co-workers145. Applications of porous silicon in the last decades have been the subject of some comprehensive reviews146-148.

1.4.2 Porous silicon photonic crystals label-free optical biosensors

As photonic crystals, multilayered porous silicon exhibits interference fringes in which a minor change can be more conspicuous than averaged features in single layered structures. Recent efforts in porous silicon sensors have almost exclusively concentrated on typical multilayer structures such as Bragg mirrors132, 149, Rugate filters150, 151 and Microcavities134, 152-154. In particular, porous silicon microcavities are a highlight in porous silicon biosensing efforts, being contributed in both experimental and theoretical aspects by Fauchet 155-158, Delouise159-162 and their colleagues163. Rugate filter structures have been demonstrated by Gooding and co-workers as a promising sensor by means of

effective surface chemistry164-166. An illustration of porous silicon microcavity sensing is shown in figure 1.6.

Figure 1.6 An illustration of porous silicon microcavity biosensors. The top graph depicts a sensor based on red shift induced by introduction of foreign species into the sensor (increased effective refractive index) while the bottom graph demonstrates blue shift type sensors where signal is inflicted by displacement of materials in the sensor (reduced effective refractive index).

Practical performance of these multilayered structures is determined by the resolution ability of the detector and the response induced by the sensing events, i.e. the magnitude of peak wavelength shift per unit of refractive index change. Although all the photonic structures mentioned in this section exhibit similar response, intrinsically, sensitivity of a structure is dictated by its physical quality factor. A minor shift on a Bragg reflector may be invisible whereas the same magnitude of shift in optical feature on a higher quality can be observed.

One study conducted by Anderson et al167 compared the sensitivity of three types of porous silicon structures (single layer, Distributed Bragg reflector, and microcavity) and found that microcavity is inferior to Bragg mirror in terms of sensitivity despite its obvious and discernible optical feature. The reason for the lower sensitivity in experiments was ascribed to poor diffusion of the target material into the porous network with sharply contrasted porosities. It is well accepted that to fully take advantage of the responses of microcavities, the analytes have to be delivered to the central layer to interact with light which repeatedly bounced between two mirrors. A study by De Stefano et al168 found that only when central layer and layers in close proximity of it are filled, can a significant optical shift be observed. Unfortunately this is hardly the case in most sensing implementation on monolithic microcavities. Enclosed cavity layer deeply embedded between two multilayer Bragg mirrors is virtually inaccessible to analytes in sensing applications. To make sensitive microcavity structures, porosity contrast between high and low porosity layer has to be high enough, which however, exerts blockade to infiltration of analytes. Simulation by Ouyang156 showed only a minor shift is induced by filling a few layers on the very top of a microcavity while an added layer on top only causes shift in sidelobes. Although it is acceptable that sensing targets do not need to infiltrate all the way to the bottom of pores, in low target concentration region, resolvability of small shift can be a challenge. Engineering of pore size and morphology by post fabrication to cater for molecular diffusion resulted in deteriorated Q-factor and subsequently, sensitivity169, 170.

Fortunately, fabrication technique of porous silicon allows us more flexibility in manipulating the layer sequence such that some new structures can be created for improved sensing performance by removing some intrinsic constraints for microcavities. A porous silicon waveguide developed by Rong et al showed 60 fold improvement in sensitivity over Surface Plasmon Resonance technique for DNA sensing171. De Stefano and co-workers reported resonant mirror based on porous silicon which exploited evanescent waves on the surface of sensor surface and demonstrated DNA sensing. Rychman et al172 proposed a porous silicon diffraction grating for low-cost biosensing. The grating was fabricated by standard stamping techniques to create corrugated patterns.

1.4.3 Moving on from microcavities

In contrast to the standing waves enclosed in a Fabry-Perot microcavity, surface waves can also exist in a photonic crystal under some circumstances and the surface waves are travelling at an interface which is more easily accessible. It has been demonstrated that in the stop band of the photonic crystal, a optical mode could exist that decays exponentially with distance from the surface o the optical device173. As will be elaborated in chapter 4, Bragg reflectors can be tailored into another class of photonic structures which localize light at the open interfaces rather than at the centre in the case of microcavities. This minor variation in structure configuration presents tremendous benefit especially as far as biosensing implementation is concerned. Sensitive dependence of the mode on its environment can be utilised to develop particular devices such as biosensors, as will be demonstrated in chapter 5. Low loss dielectric material, flexible and easy fabrication make porous silicon surface wave structure a promising sensing platform and potentially superior alternative. Photonic crystal based surface wave sensors are complementary to Surface Plasmon Resonance (SPR) techniques, and sustained by structurally engineered porous silicon multilayers, as demonstrated in this thesis, allow us to probe the entire surface layer of the porous architecture and utilize highly functional and robust silicon based surface chemistry.

1.4.4 Surface chemistry: a key to reliable, functional, selective and robust sensors

While pursuit for biosensing applications of porous silicon has been focused more on novel structures that can promote analyte-sensor interaction and signal readout, the degradation of intrinsically reactive and unstable surface resulting from wet etching is an obvious issue to be addressed if the further exploration of sensitive, reliable and more robust devices are to be made. Biosensing applications in particular, require a specific, selective interface to capture the analytes of interest. The sensor devices need to withstand physiological conditions which are harsh for most materials used in sensor construction. In chapter 4, a number of surface chemistry schemes used for porous silicon surface stabilisation and derivatisation will be discussed with organic monolayer based on Si-C bonding highlighted.

1.5 Other applications of porous silicon 1.5.1 In vivo sensors

Besides widely studied in vitro sensing platforms, the inherent nature of luminescence, biodegradability and biocompatibility and convenient surface chemistries enable the use of porous silicon as an in vivo sensing vehicle such as subcutaneous or implantable sensors151, 174-176. As an outstanding example, luminescent microparticles emerge as a candidate for in vivo sensor, as was introduced by Sailor et al177. Meanwhile, some attempts have been made to exploit the passive optical properties of porous silicon photonic crystals by measuring reflectance on single particles as small as 5 μm for the purpose of single cell sensing 178.

1.5.2 Drug delivery

Additionally, tailored porous silicon structures and device dimensions aiming for other in vivo applications are being explored. One particular respect of biomedical applications is drug delivery. Large internal surface area, precisely tunable pore size and morphology and diverse surface engineering possibilities provide an ideal host and carrier for various drugs179-182. What is most attractive aspect of porous silicon as a self- reporting drug conveyer is the possibility of controlled release and real-time monitoring thanks to its sensing capability183, 184. Low toxicity, and the fact that porous silicon tends to degrade into bioavailable material orthosilicic acid (Si (OH)4 ) have led to extensive work on porous silicon towards clinically practical delivery systems18, 185, 186.

1.5.3 Cell cultivation and tissue engineering

Porous silicon has also been investigated as a tissue engineering scaffold in osteoconstructive repair and therapy for the benefit from inherent osteoconductivity and osteoinductivity187-189. Moreover, the possibility to control porous silicon devices via optical or electrical stimulation in order that the device can selectively capture cells and adjust cellular behaviour to facilitate tissue regeneration, which can also be assisted by controllable release of drugs pre-loaded in porous silicon190, will open up a very promising pathway to interactive sensing and intervention over the physiological activities in medical diagnosis and therapy.

1.6 Summary and the outline of the thesis

In summary, I have introduced the concept and associated merits of label free optical biosensors based on a refractive index modulation of integrated photonic architectures. In particular I have focused on the use of the material porous silicon as a versatile platform for creating periodically modulated one-dimensional photonic structures that are suitable for optical biosensing applications. I have reviewed the process of fabricating porous silicon and how controlling the nanostructured morphology of the films is critical in achieving optical films with sharp resonant spectral features.

The thesis is organised as following:

Chapter 1 is an introduction to the background and current status of research activities in porous silicon photonic crystal and its applications in optical, optoelectronics devices and optical biosensors. The introduction starts with the formation mechanism and geometry-based categorisation of porous silicon, followed by its optical properties ranging from photoluminescence to advantageous characteristics of porous silicon as mesoporous photonic crystal. Structural and surface engineering porous silicon multilayer structure for versatile and specific functionalities is also mentioned in this chapter. Research on biosensing applications of porous silicon is reviewed and new directions in this aspect are envisaged.

In chapter 2, materials, general methods and techniques used to fabricate, modify, characterise porous silicon structures are introduced. In addition to the experimental techniques, numerical methods used in the study are also described.

Chapter 3 depicts the construction and characterisation of quantum doped porous silicon microcavities. Instead of monolithic fabrication, a microcavity is formed by joining two porous silicon Bragg reflectors together. Strong and specific molecular interaction between biotin and its complementary partner streptavidin is utilized to selectively immobilize colloidal quantum dots on one of the Bragg reflectors and such a biomolecular affinity ultimately facilitates the formation of a hybrid porous silicon microcavity embedded with quantum dots in the central layer. Optical properties of porous silicon microcavity doped with II-VI colloidal quantum dots were studied in detail. Photoluminescence emission of quantum dots is enhanced by a factor of 30 and

narrowed from 80 nm to 2.5 nm. Spatial modification effects such as directional concentration and angular dependence are observed. What is more, resonance wavelength and subsequent emission from the microcavity can be tuned in a range of 20 nm simply by infiltrating the structure with glycerol aqueous solution.

Chapter 4 details the fabrication and characterisation of a new type of porous silicon structure for biosensing purpose. The design of the sensing platform is based on porous silicon one dimensional Bragg reflectors. As the Bragg reflector is truncated outmost, evanescent surface electromagnetic wave is observed as a dip in the reflectivity spectra in the stop band of the Bragg reflector. Impact of truncation, thickness of the outmost layer and the number of layer pairs on the surface mode are studied. Numerical simulation is used to verify the structure fabricated. Well established surface chemistry for porous silicon is carried out and results in a sensor interfaced with gelatin. Thanks to the size exclusion effect of the Bragg mirror, gelatin is only grafted in the top layer of the structure, implying the sensing reaction will only occur in this layer. Surface chemistry is monitored with reflection measurements.

It is exhibited in chapter 5 that porous silicon surface wave sensor demonstrated in chapter 4 has the ability of protease detection. Gelatin grafted Bloch surface wave sensors are used to probe the protease. Detection of protease is accomplished by exploiting a linear relationship between the rate of optical change and the enzyme concentration at the early stage of the enzyme reaction. Such a linear dependence also indicates that on the sensor surface is dominantly mediated by Michaelis-Menten kinetics which is observed in an intermittent fashion. Open sensing space of the sensor format suggests the necessity and feasibility of continuous kinetics monitoring by incorporating fluidic system.

Chapter 6 summarises the efforts the author made in microcavity biosensors to address constraints associated with mass transport restriction in the all porous silicon structures. The sensor is designed as a sandwich structure with a separate spacer, made up with protein, surrounded by two porous silicon Bragg reflectors. High quality microcavity structures are successfully manufactured with satisfactory reproducibility. An innovation in the optical measurement removes the mess of distorted spectra and enables continuous monitoring of the cavity mode evolution. The concept exhibits a

sensitive response to protease activity which is, at present, subject to unpredictable responses related to disintegration of the structure on exposure to aqueous solution. Some possible measures to stabilize the structure are pointed out in this chapter.

The thesis is concluded in chapter 7 with some outlook for porous silicon biosensor platform proposed in the thesis envisaged.

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185. Dondapati, S.; Sri, A. P., NANOSTRUCTURED POROUS SILICON–A NOVEL BIOMATERIAL FOR DRUG DELIVERY. International Journal of Pharmacy and Pharmaceutical Sciences 2009, 1, (2), 8-16. 186. Salonen, J.; Kaukonen, A. M.; Hirvonen, J.; Lehto, V.-P., Mesoporous silicon in drug delivery applications. Journal of Pharmaceutical Sciences 2008, 97, (2), 632-653. 187. Canham, L. In Porous silicon as a therapeutic biomaterial, Microtechnologies in Medicine and Biology, 1st Annual International, Conference On. 2000, 2000, 2000; 2000; pp 109-112. 188. Coffer, J. L.; Whitehead, M. A.; Nagesha, D. K.; Mukherjee, P.; Akkaraju, G.; Totolici, M.; Saffie, R. S.; Canham, L. T., Porous silicon based scaffolds for tissue engineering and other biomedical applications. physica status solidi (a) 2005, 202, (8), 1451-1455. 189. Sun, W.; Puzas, J. E.; Sheu, T.-J.; Fauchet, P. M., Porous silicon as a cell interface for bone tissue engineering. physica status solidi (a) 2007, 204, (5), 1429-1433. 190. Sun, W.; Puzas, J. E.; Sheu, T. J.; Liu, X.; Fauchet, P. M., Nano-to microscale porous silicon as a cell interface for bone-tissue engineering. Advanced Materials 2007, 19, (7), 921- 924.

Chapter 2 Experimental setups and procedures 2.1 Materials and reagents

Chemicals, reagents and materials used in this research are listed in table 2.1.

Items Structure or Grade Source specification

Silicon wafers 2.5 inch in diameter, single Semiconductor Institute of polished, highly boron-doped, Electronic Materials ‹100› oriented, p+ type, Technology (ITME, resistivity 1.5-2 mΩ cm Warsaw, Poland) Ethanol absolute AR Ajax Fine Chemicals Acetone 99.5 % AR Ajax Fine Chemicals Pentane 99.0 % AR Ajax Fine Chemicals Hydrofluoric acid 48% aqueous, diluted to AR Ajax Fine Chemicals concentration with ethanol depending on designated usage High purity water Resistivity 18.2 MΩ cm-2 Milli Q grade Milli Q water reagent filtering system Bovine serum CAS 9048-46-8, lyophilized NA Sigma-Aldrich albumin powder, Dissolved in PBS buffer (pH 7.4) Biotinylated Lyophilized powder, NA Sigma-Aldrich bovine serum Dissolved in PBS buffer (pH albumin 7.4) Colloidal 1 μM solution in 1 M betaine, NA Invitrogen Australia quantum dots 50 borate, pH 8.3 with 0.05 % Pty Ltd. Streptavidin sodium azide. conjugate Streptavidin CAS 9213-20-1 NA Sigma-Aldrich Agarose

Undecylenic acid (CH2=CH (CH2)8–COOH) NA Sigma-Aldrich

N-ethyl, N’-(3- CAS 1892-57-5 NA Sigma-Aldrich dimethylaminopro H3C N+ CH N CNCH CH pyl)-carbodiimide 2 3 2 3 H3C (EDC) 1 1-amine-hexa- O Synthesized H ethylene glycol H2N 6

N- CAS 6066-82-6 Sigma-Aldrich hydroxysuccinimi OH de (NHS) O N O

N,N- CAS 1122-58-3 Sigma-Aldrich dimethylaminopyr N idine (DMAP)

N,N'- CAS 74124-79-1 Sigma-Aldrich disuccinimidyl O O O carbonate (DSC) N N OO O O Gelatin Low bloom powder, 22-25 Sigma-Aldrich kDa Gelatin Medium bloom powder, 40-50 Sigma-Aldrich kDa Subtilisin CAS 9014-01-1. Lyophilized Activity: 7-15 Sigma-Aldrich (Carlsburg) powder, Dissolved in PBS units per mg buffer (pH 7.4) at 10 mg/ml as solid3. the stock. Dilute freshly to desired concentration before use PBS buffer (1×) NaCl 137 mmol/L, KCl 2.7 Routinely prepared2

mmol/L, Na2HPO4 10.0mmol/L,

KH2PO41.76mmol/L

1: Synthesized by Bin Guan as described in ref 1

2: Prepared by dissolving 8 g NaCl, 0.2g KCl, 1.44 g Na2HPO4, 0.24 gKH2PO4 in 800ml water. Adjust to pH7.4 with 0.1 M HCl or NaOH. Make up to 1 L.

3: Activity was assayed with ninhydrin colorimetric method using gelatin as the substrate1.

2.2 Fabrication of porous silicon 2.2.1 Electrochemical etching of silicon

Silicon wafers were cleaved into square pieces of 1 cm, cleaned in acetone and ethanol under ultra-sonication for 5 min respectively. Electrochemical etching of silicon was undertaken in galvanostatic mode (constant current). A schematic diagram shown in figure 2.1a illustrates the setup used in electrochemical etching, while figure 2.1b is a schematic of the etching cell configuration.

Figure 2.1 a) Schematic diagram of electrochemical etching cell. b) Cross-sectional diagram of etching cell.

For room temperature etching, in order to obtain a mesoporous network (hereafter in this thesis) with the largest porosity contrast, 25% (V/V) hydrofluoric acid solution, made by mixing equal volumes of concentrated HF and absolute ethanol was used as the etchant. Layers with different porosities were created by applying distinct current densities, as is illustrated in Figure 2.1a (green pulses). The thickness of a layer is determined by the duration of the current pulse. In order to form a homogeneous layer, a pulse is broken into a few sub-units divided by intervals of zero current (not shown in Figure 2.1a). Abrupt termination of current pulses leads to layer-to-layer interfaces as the etching is a self-controlled. Inclusion of ethanol in the electrolyte composition reduces the bubble sizes of hydrogen generated in the etching process and hence helps to discharge H2 bubbles from the electrolyte, making sure etching continues homogeneously. To obtain sharper interlayer interfaces, so that scattering losses will be minimised and therefore a sharper optical mode with higher finesse can be achieved, Bragg reflectors were also fabricated at low temperature (-20ƷC). At low temperature etching condition, an electrolyte containing 35 % HF, yielded a wider porosity range (27%-80%) so 35 % HF ethanolic solution was employed for low temperature operation. A Teflon laminated thermocouple was used to monitor the temperature. At low temperature, minor fluctuations have significant impact on the etching process, so temperature fluctuation in the etching process must be controlled within r2.5ƷC. To minimise the impact of increased viscosity of the etchant solution at low temperature on the etching process, more frequent and longer breaks were interposed during etching to allow the escape of H2 bubbles that block the contact of electrolyte and silicon surface. Breaks also help regeneration of F- concentration at the etching front so that etching proceeds at a uniform rate. A custom etching cell is designed such that a limited area of 0.95 cm2 was exposed to the electrolyte. Etching was performed in the dark, secured by a cover that holds the platinum ring submerged in the electrolyte as a counter cathode.. Constant current pulses were generated by a current source supplier and monitored with a multimeter. An oscilloscope was also used to verify the current and its variation. The whole etching process including current value, current pulse generation, termination and duration was controlled by a Labview programme on a computer linked to the source meter and the oscilloscope, respectively.

As has been introduced in the previous section (1.2), porous silicon formation is sensitively governed by the applied current density. Under fixed material conditions (wafer type, electrolyte composition, temperature, etc.), porosity increases with current density while etch-rate is proportional to current density. The dependence of porosity on the applied current, obtained on the wafers used in this thesis, is shown in figure 2.3. Also shown in the figure is the linear dependence of etch-rate on the current (density).

Figure 2.2 Relation between porosity and etch rate and applied current on highly boron doped p+ silicon (orientation ‹100›, resistivity 1.5-2 mΩ.cm) in 25% hydrofluoric acid ethanolic solution as etchant at room temperature. Porosity increases steeply with current in low current range. Etch rate increases linearly with current.

2.2.1.1 Fabrication of porous silicon microcavities

For microcavity formation, two Bragg reflectors were etched with a layer sequence of

(LH)n(HL)n, where H denotes high porosity (low refractive index) layer and L stands for low porosity (high refractive index) layer. The two high porosity layers at the centre of the structure forms the half-wavelength cavity layer. To maximize the refractive index contrast and obtain mechanically stable multilayer stacks, a current of 5 mA was used to produce a porosity of approximately 44%, high porosity layers were produced with a current of 220 mA, equivalent to a current density of 232 mA/cm2, which is capable of 36 creating a high porosity of approximately 80%. Low temperature etching is undertaken at -20 f2.5˚C in a temperature controlled freezer. A current pair of 12 mA and 127 mA was used to create maximum contrast of low porosity (27 %) and high porosity (82 %).

Bragg reflectors used in this thesis are in a sequence of (HL)n, with n= 5 or 6. When the two Bragg reflectors combine together to form a microcavity, two high porosity layers form the cavity layer. Etching time for microcavities with resonance wavelengths at 565 nm, 625 nm, and 780 nm are listed in table 2.2.

Table 2.2 Expected porosities of component high and low porosity layers and applied etching conditions (current and etching time)

Resonance wavelength, nm Porosity, % Current, A Etching time, ms/layer H, % 80 0.22 1050 565 L,% 44 0.005 13000 H, % 80 0.22 1250 625 L,% 44 0.005 16800 H, % 80 0.22 1480 780 L,% 44 0.005 24600

2.2.1.2 Fabrication of Bloch surface wave sensors

To fabricate structures used for Bloch surface wave biosensors, a high porosity layer was etched on top of a Bragg reflector with layer sequence of (LH)4, where L was a layer with porosity of approximately 44%, produced by a current of 0.005 A; while H was a layer of 75% porosity, formed by a current of 0.15 A. Etching time for high porosity and low porosity layer were 1.93 s and 18.2s, respectively. For the top layer etching time was 25.4 s. Different etching time from that for the bulk Bragg reflector component layers was used so that this irregular layer serves as the sensing layer which supports a Bloch surface mode. The overall layer sequence of Bloch surface wave sensor is A (LH) 4. Layer sequence and corresponding current profile for Bragg reflector and surface wave sensor formation are shown in figure 2.3b.

Figure 2.3 ) Illustrated sequence of a 6 period Bragg reflector. b) Illustrated layer arrangement of structure used for Bloch surface wave biosensors. c) and d) depict the current profiles used to generate the layer arrangements in a) and b), respectively. Short, high current pulses produces high porosity layer while low porosity layer is formed by long and low current durations.

2.2.2 Microcavities assembled from free-standing porous silicon

In order to construct the hybrid microcavities, as will be discussed in chapter 3, at least one of the two Bragg reflectors has to be made free-standing. Multilayers used for Bloch surface wave sensors must be detached from silicon substrate so that prism light coupling can be implemented via a transparent support and refractive index matching medium. Detachment of porous silicon thin film is accomplished by a lift-off technique.

It has been found that a much higher porosity can be created in diluted HF medium. There exists a transition from porous silicon formation to electropolishing when electrochemical dissolution of silicon is performed in low concentration of electrolyte. This transition is supported by a threshold polishing current (Jps) in the i-V curve (1.2 of this thesis) that is used to describe the electrochemical process of silicon,

38 corresponding to the electropolishing current2. Porous silicon lift-off is in effect an electropolishing process when the etching current exceeds a threshold (polishing current Jps)3, the resultant porosity is too high to survive as an entity. As a consequence, the substrate is polished rather than porosified. Lift-off took place in the same cell as that used for etching. After etching, concentrated HF was removed from the etching cell and replaced with 15% ethanolic HF solution. A current of 0.32 A was applied in a 200 ms pulse to lift the thin film off the silicon substrate but remain attached to silicon at the outer rim. To completely detach the porous silicon film, a scalpel is used to disrupt the connection at the rim in ethanol. Free-standing porous silicon is carried by a piece of filter paper for further modification and reversal. In some instances, detached porous silicon thin film was moved over onto the host substrate in ethanol.

In the quantum dot doped microcavity study, a second Bragg reflector was usually lifted off and reversed onto the first one. However, the bottom mirror can also be lifted off as described above and placed on a piece of transparent substrate before quantum dots deposition and microcavity assembly such that it serves as the input mirror while emitted light comes out of the top mirror. After etching, the surface wave structure was lifted off and subjected to surface modification and functionalisation, as will be detailed in the following subsection.

2.3 Surface modification and functionalisation of Bloch surface wave structures

Surface modification and functionalisation of porous silicon Bloch surface wave sensors were depicted as scheme2.1:

Scheme 2.1 Schematic surface modification and functionalization chemistry processes adopted in the study 2.3.1 Hydrosilylation of porous silicon

The following work was done courtesy of Ms Bin Guan.

Surfaces of freshly etched porous silicon are terminated with hydrogen in the form of Si-H bond. Hydrosilylation was initially established to replace the silicon hydride (Si- Hx, x=1, 2, 3) terminated surface with alkyl or alkenyl chain through Si-C bond formation on planar silicon4, 5 and has been adapted to porous silicon as a passivation and functionalization scheme6-8 and silicon nano-particles9. Hydrosilylation of porous silicon mainly involves the reaction of alkenes or alkynes at the non-oxidized hydrogenated silicon surface assisted by heat, illumination, or microwaves. A hydrosilylation reaction can be symbolized as scheme 2.2:

Scheme 2.2 Illustration of hydrosilylation of porous silicon. Reaction employs either alkene or alkyne as the organic material and can be initiated by heating, illumination, microwave or catalysis.

The hydrosilylation reaction developed by Böcking et al10, 11 was implemented to replace the native Si-H bond with stable Si-C bond by thermal reaction on the surface with carboxylic group ended alkene molecule undecylenic acid. A home designed Schlenk flask is dried on flame and kept under argon atmosphere on argon/vacuum line. After adding undecylenic acid (neat), a number of freeze/thaw/vacuum cycles are executed until no more bubbles were generated under vacuum stage, indicating complete elimination of oxygen in the reaction atmosphere. Ultimately the Schlenk flask is kept under the slightly positive pressure of high purity argon gas, ready for the sample loading. Freshly etched and lifted porous silicon (attached at rim) is gently placed in the flask under argon. The flask was sealed and heated to 160ƷC and kept at this temperature for 12-16 hours. After the reaction sample is taken out from the flask and washed with dichloromethane and ethyl acetate and dried in a mild argon gas flow.

2.3.2 Formation of anti-fouling molecule layer

The distal carboxylic group is activated with N-hydrosuccinimide (NHS) in the presence of coupling agent N-ethyl, N’-3-(3’-(dimethylamino) propyl) carbodiimide (EDC). Before the sensing element gelatin is attached, the surface reacts with 1-amino-hexa (ethylene glycol, OEG) in order to form an antifouling layer to eliminate the nonspecific adsorption of proteins and their derivatives in the sensing process. OEG functionalised device is cut off from silicon on the rim and placed on a piece of No.2 glass coverslip.

2.3.3 Gelatin immobilisation

In order to immobilise gelatin as the sensing element, the ethylene glycol terminated film is activated by immersing in with 0.1 M N, N'-disuccinimidyl carbonate (DSC) containing 0.1 M N, N -dimethylaminopyridine (DMAP) for 12 - 24 hours. The modified porous silicon optical structure was rinsed with ethyl acetate and CH2Cl2 and blown dry under a stream of argon before gelatin coupling by covering the device with 10 mg/ml gelatin aqueous solution in PBS. The completed device is put on a prism via refractive index matching oil to facilitate light coupling.

2.4 Optical characterisation of porous silicon

2.4.1 Reflectivity

2.4.1.1 Normal incident reflectivity measurement

Reflectivity measurement of porous silicon microcavities are performed on a custom- built setup shown in figure 2.5. The porous silicon sample is placed on a horizontal stage which can be adjusted in x, y, and z direction, using a micro-positioner. The levelness of the stage can also be adjusted. A halogen white light source is collimated using a lens and a variable aperture. A portion of the light beam is focused with a focus lens and directed with a mirror onto the surface of the device at an incidence angle close to normal. To probe the inhomogeneity of on the sample surface, a beam size of 50 μm is formed on the sample. Reflected light is redirected with the mirror, collimated with the same lens, focused with a lens, and collected by an objective and coupled to Ocean Optics USB+ 2000 spectrometer (resolution = 1 nm) via optical fibre. A cubic light beam splitter is used to direct the source light beam and guide the reflected light beam. A piece of silicon is used as reference to obtain normalized reflectance.

Figure 2.5 Normal incidence reflectivity measurement set up. White light is split and focused onto porous silicon sample surface in order to create a beam spot of approximately 50 μm to distinguish the inhomogeneity across the sample area. The setup is open for integration of photoluminescence measurement at normal and variable detection angles.

Apart from the above approach, the bottom mirror can also be placed on a transparent substrate after lifting off and the resultant microcavity is supported by the transparent substrate so that the probing light can be incident from the back rather than the front of the structure.

2.4.1.2 Simulation of multilayered porous silicon

Effective Medium Approximation is an important tool in design and optimization of nanostructured composite materials. Numerical simulation based on the approximated effective refractive index is widely employed to predict optical properties of multilayered photonic crystals.

2.4.1.2.1 Effective Medium Approximation (EMA) methods

After electrochemical dissolution, bulk crystalline silicon is turned into the mixture of columnar silicon and air filling the void left by etching. Since the silicon clusters in mesoporous silicon are much smaller that the wavelength of light, porous silicon appears to be a homogeneous material with distinct effective dielectric constant. Essentially effective medium theory considers a dielectric mixture of two components 43

of a nanostructured composite material as a host (dielectric constant εM) and an embedded material (dielectric constant ε). The effective dielectric constant of the mixture is used to represent the apparently homogeneous medium. With the aid of computing technology, a number of numerical models have been established with different averaging algebra are available for simulation and prediction of optical properties of porous silicon. Typical effective medium approximation (EMA) models are listed in table 2.312, 13.

Table 2.3 Typical EMA numerical models used for porous material characterisation

Model Formalism Application

߳௘௙௙ െ߳ெ ߳െ߳ ൌሺͳെ݌ሻ ெ Spherical particles in Maxwell-Garnet ߳௘௙௙ ൅ʹ߳ெ ߳൅ʹ߳ெ the media

߳ெ െ߳௘௙௙ ߳ெ െ߳௘௙௙ ݌ ൅ ሺͳെ݌ሻ ൌͲ Mixture of the Bruggerman ߳ெ ൅ʹ߳௘௙௙ ߳ெ ൅ʹ߳௘௙௙ spherical particles

Consideration of optical homogeneity and relatively small differences between dielectric functions of the components; the influence of the Looenga- sample

Landau- Lifshitz ଵൗ ଵ ଵൗ microtopology ଷ ൗଷ ଷ (3L) ߳௘௙௙ ൌሺͳെ݌ሻ߳ ൅݌߳ெ neglected.

As is stated in the table, 3L or Looenga model can give more reliable approximation of dielectric constant of porous silicon as it takes morphological factors into account in modelling, as has been successfully demonstrated in porous silicon fabricated from p+- type substrate14. A Looenga model involving multiple components is expressed as13:

ଶȀଷ ଶȀଷ ݊௘௙௙ ൌ෍݂௜ ݊௜ ௜

fi is the fraction of individual components, ni is their respective refractive indices, ݊ൌξ߳ߤ . For most materials with light in the optical range, μ≈1. It will be very useful in estimating effective refractive index of porous silicon with modified surface and help predict the optical footprint (evolution of the optical feature of the sensor in response to

44 activities on the sensor, such as molecular binding, cleavage, and sensor surface degradation) of surface modification and subsequent effects such as biological recognition or non-specific variation such as oxidation. It also serves as an effective tool in designing structures and correcting drifts in etching conditions. Looenga model can be extended to average the dielectric constants involving multiple components, as in the case of chemical modification, and sensing operation15.

2.4.1.2.2 Transfer Matrix Methods (TMM)

Transfer matrix method, based on Maxwell’s equation, is a widely used to describe propagation of electromagnetic wave in a multilayered medium. 1-D TMM considers a system containing a finite number of component layers with an individual layer regarded as an optically isotropic medium with distinct thickness and refractive index specific to the wavelength. Because of its microscopic inhomogeneity and apparently stratified phase variation, enabled by the unique self-controlled formation process and precise correlation between porosity and current density applied in fabrication, porous silicon largely resembles a multi-thin films structure with well defined interfaces and optical flatness. In principle, based on effective refractive index and thickness estimated by EMA method, major features of reflection and transmission of light can be predicted by solving Maxwell’s equations in consideration of boundary conditions. As has been demonstrated by Reece 16 reflection and transmission of waves in porous silicon multilayer structures can be simulated in good agreement with experimental results. Considering the isotropic nature of porous silicon at optical wavelengths, the individual layers can be characterised by an effective refractive index and reflectivity of multilayered structures at arbitrary incidence can also be studied with TMM. The simulation programme used in this study is based on TMM method.

Typical simulations of a) single layer, b) Bragg reflector and c) a microcavity structure are shown in figure 2.6.

Figure 2.6 Simulation of optical features in a porous silicon single layer (a), Bragg reflector (b) and (c) microcavity based on transfer matrix method.

2.4.2 Photoluminescence measurement

Photoluminescence measurement is performed on a home-made setup described by Reece16 using 514.5 nm line of argon ion laser. The argon laser was focused on the porous silicon sample with a 15 cm focal length lens to create an excitation beam spot of approximately 50 μm. Photoluminescence emission was collected using a 0.27 m focal length spectrometer (J/Y SPEX 270M) with a thermoelectrically cooled charge coupled device (CCD). The setup used for PL measurement is schematised in figure 2.7.

Figure 2.7 Schematic of experimental setup for photoluminescence measurement. Photoluminescence could also be simultaneously monitored on the reflectivity setup as schematized in figure 2.8. A 440 nm Coherence Cube diode laser (with a power of 16 mW) was integrated into the reflectivity measurement setup illustrated above so that the laser beam was focused onto the sample surface with a focus lens to create a light spot overlapping the white light beam spot in reflectivity measurement. PL emission was directed and collected with optics of reflectivity measurement and acquired with Ocean Optics Suite software.

Figure 2.8 Photoluminescence measurement setup using diode laser as probing light incorporated into normal incidence reflectivity set.

2.5 Optical characterisation of porous silicon surface wave biosensors 2.5.1 Spectral reflectivity measurement

Spectral reflection measurement of polarized light on porous silicon based Bloch surface wave biosensor is performed on a setup with prism coupling configuration (Krestchman configuration), widely used in SPR instrumentation. A white light is used as the probing source. A fibre-coupled white light is collimated to a 10 mm-diameter beam and passed through a polarizing beam splitting cube to produce a TE polarized (s) incident light beam. The incident beam is focused with a 10 cm focus lens and directed with a mirror that light beam coupled into the into the internal reflection surface of the sensor has an incident angle of 45Ʒand the size of incident light beam on the sample surface is of the order of 100 μm. The Krestchman configuration was used in this thesis in order to achieve reliable and controllable light coupling. Sensor chips mounted on glass substrate were placed on a BK7 right angle prism (refractive index 1.52 at 631 nm), intermediated by refractive index matching oil. Figure 2.9 depicts the detailed diagram of sensor sample mounted on the top of surface of the prism using appropriate refractive index matching oil (refractive index 1.5660). A blank glass coverslip was used as a reference to correct the spectral sensitivity of the system.

Figure 2.9 Diagram of the Kretschmann-type prism coupling optical arrangement used for measuring the reflectivity of the surface wave sensor. The incident white light was polarized in the TE orientation and focused onto the prism using a 10 cm focal length lens. The reflected light is collected by a second lens and coupled to a spectrometer.

Light reflected from the sample is guided with a mirror and collected with a second lens and coupled into the Oceanic Optics 2000+ spectrometer using a fibre coupler. The acquired data are plotted with Origin 6.1 software.

2.5.2 Enzyme test on BSW sensors

To baseline the sensor on hydrated gel, sensor ships were hydrated with phosphate buffer saline (PBS) for 5 minutes. After removing PBS with a small piece of filter paper, 5 μl of water was spotted on the sensor surface and left for 5 min in order to remove salt residue on the sensor internal surface left by PBS hydration. Water was removed and the chip exposed to air for 10 min before a reflectivity spectrum was taken for the initial status of enzyme test. Spectra are registered after PBS hydration and water rinse. All tests are performed at room temperature.

2.5.2.1 Protease detection

On the hydrated and rinsed sensor surface, an aliquot of subtilisin solution (in PBS) diluted from 10 mg/ml stock is spotted and left for a fixed period of time. Volume of enzyme solution and the reaction time varied for different enzyme concentrations. To maintain a solid/liquid interface for the enzyme reaction, sensor chips were covered to prevent the evaporation of water. At the end of reaction, excessive solution was removed with a piece of filter paper. Reflectivity spectra were taken 10 min after the filter paper dried up and removed. The sensor chip was rinsed with an aliquot of water for 5 min and removed with a piece of filter paper. Reflectivity spectra were registered again 10 min after the removal of dried filter paper. During the test the sample is fixated on the top of the prism in order to eliminate minor variations due to the lateral inhomogeneity across the sensor surface, particularly at low enzyme concentration levels.

2.5.2.2 Enzymatic kinetics monitoring

Due to the surface waves in the underlying design are launched at the dielectric-air interface, all optical measurements are restricted to the condition when enzyme solution is removed. Enzymatic reaction kinetics is discontinuously monitored as following steps:

1) The sensor chip was hydrated and spotted with enzyme solution and started timing;

2) After the first scheduled time elapsed, enzyme solution was removed to stop the reaction and the sensor was rinsed with 5 μl of water for 5 min. After water removal, sensor chip was left in air for 10 min before reflectivity spectrum was registered;

3) The enzymatic reaction was resumed by spotting another aliquot of enzyme solution on the sensor chip. Reaction was manipulated in the same way as in step 2, whereas suspended at the second check time point such that the sum of the time of enzyme exposure recorded in all reaction sessions so far amounted to the scheduled accumulative reaction;

4) Step 3) was repeated until the total accumulative time of enzyme exposure was reached as scheduled. References

1. Kilian, K. A. Chemical and biological modification of porous silicon photonic crystals. University of New South Wales, Sydney, 2007. 2. Rauscher, M.; Spohn, H., Porous silicon formation and electropolishing. Physical Review E 2001, 64, (3), 031604. 3. O Garel, C. B., E Dufour-Gergam, A Bosseboeuf, B Belier, V Mathet and F Verjus, Fabrication of free-standing porous silicon microstructures. J.Micromech.Microeng. 2007, 17, S164-S167. 4. Linford, M. R.; Chidsey, C. E. D., Alkyl monolayers covalently bonded to silicon surfaces. Journal of the American Chemical Society 1993, 115, (26), 12631-12632. 5. Sieval, A. B.; Demirel, A. L.; Nissink, J. W. M.; Linford, M. R.; van der Maas, J. H.; de Jeu, W. H.; Zuilhof, H.; Sudholter, E. J. R., Highly Stable Si-C Linked Functionalized Monolayers on the Silicon (100) Surface. Langmuir 1998, 14, (7), 1759-1768. 6. Buriak, J. M., Functionalization of Silicon Surfaces for Device Applications. Journal of the Association for Laboratory Automation 1999, 4, (3), 36-39. 7. Boukherroub, R.; Wojtyk, J. T. C.; Wayner, D. D. M.; Lockwood, D. J., Thermal hydrosilylation of undecylenic acid with porous silicon. Journal of the Electrochemical Society 2002, 149, H59. 8. Buriak, J. M.; Allen, M. J., Lewis acid mediated functionalization of porous silicon with substituted alkenes and alkynes. J. Am. Chem. Soc 1998, 120, (6), 1339-1340. 9. Nelles, J.; Sendor, D.; Ebbers, A.; Petrat, F. M.; Wiggers, H.; Schulz, C.; Simon, U., Functionalization of silicon nanoparticles via hydrosilylation with 1-alkenes. Colloid & Polymer Science 2007, 285, (7), 729-736. 10. B cking, T.; Wong, E. L. S.; James, M.; Watson, J. A.; Brown, C. L.; Chilcott, T. C.; Barrow, K. D.; Coster, H. G. L., Immobilization of dendrimers on Si-C linked carboxylic acid- terminated monolayers on silicon (111). Thin Solid Films 2006, 515, (4), 1857-1863. 11. B cking, T.; Kilian, K. A.; Gaus, K.; Gooding, J. J., Modifying Porous Silicon with Self-Assembled Monolayers for Biomedical Applications: The Influence of Surface Coverage on Stability and Biomolecule Coupling. Advanced Functional Materials 2008, 18, (23), 3827- 3833. 12. W.Theiβ, Optical properties of porous silicon. Surface Science Reports 1997, (29), 91- 192. 13. Alekseev, S. A.; Lysenko, V.; Zaitsev, V. N.; Barbier, D., Application of Infrared Interferometry for Quantitative Analysis of Chemical Groups Grafted onto the Internal Surface 50 of Porous Silicon Nanostructures. The Journal of Physical Chemistry C 2007, 111, (42), 15217- 15222. 14. Squire, E. K.; Snow, P. A.; Russell, P. S. J.; Canham, L. T.; Simons, A. J.; Reeves, C. L., Light emission from porous silicon single and multiple cavities. Journal of Luminescence 1998, 80, (1-4), 125-128. 15. Chapron, J.; Alekseev, S. A.; Lysenko, V.; Zaitsev, V. N.; Barbier, D., Analysis of interaction between chemical agents and porous Si nanostructures using optical sensing properties of infra-red Rugate filters. Sensors and Actuators B: Chemical 2007, 120, (2), 706- 711. 16. Reece, P. J. High-Quality Mesoporous Silicon Optical Structures. University of New South Wales, Sydney, Australia, 2004.

Chapter 3 Optical properties of quantum dot doped porous silicon microcavities

In this chapter the author will describe a new technique to build up porous silicon microcavities. More specifically, fabrication and characterisation of active optical devices assembled with porous silicon photonic crystal building blocks will be discussed. I will propose an approach to building up light emitting microcavities by selectively embedding functionalised colloidal quantum dots between two porous silicon Bragg reflectors through biomolecule oriented assembly in a stepwise manner. Instead of monolithic structure exploitation, fabrication of 1-D microcavities devices involves the strong affinity forces between biological complementary partners that are thermodynamically favourable and highly specific. Incorporating quantum dots during the fabrication of the microcavity leads to modification of the light emitting properties of quantum dots including spectral narrowness, intensity enhancement, and spatial concentration of emission pattern. Development of silicon based devices meets the demand for optoelectronics applications and integration compatibility criteria. Microcavities assembled in this way allow dynamic tuning of optical properties by simply introducing foreign substances into the porous network. Tuneable properties are a congenital and valuable merit of porous silicon photonic crystals and afford potential in a wider range of device applications such as optical modulators, switches, photodetectors, energy converters, and light sources. More importantly, as an ideal candidate for biosensors, porous silicon sensing devices can be built up with separately chosen material as central layer in order to specifically target analytes of interest. Enhanced, narrowed and tunable emission from microcavities implies promising prospect in implementing biosensing on porous silicon in photoluminescence modality.

3.1 Acquiring light from silicon

Silicon, a backbone material in microelectronics industry, hasn’t played a defining role in integrated optoelectronics. The reason silicon is less popular than in microelectronics technology lies in the intrinsic inability of silicon to make light emitter to meet the demand for optoelectronics and optical communications as silicon is an indirect band

52 gap material. On the contrary, it has been somehow standing aside and taken over by compound semiconductors such as InAs, InP and GaAs etc. which have direct band gap and thus are more efficient emitters. Unfortunately these materials are expensive. It is difficult to integrate devices made from these compound semiconductors into silicon based chip due to their larger crystal lattice constant than silicon. The dominance of silicon in microelectronics unremittingly injected impetus into the search for ways to achieve Si based light emitting devices (LEDs). Huge efforts have been devoted into research on light emitting efficiency improvement on silicon of small size scale, such as, nano-crystal silicon and porous silicon 1-3so that visible emission can be obtained from expanded band gap (2-3eV for silicon nano-crystals compared with 1.12eV for silicon).

An important way to create silicon nano-crystals is embedding Si into SiO2 to form stable luminescent silicon rich in silicon oxide (SRSO) nanocrystals using techniques such as ion implantation4. Silicon nanocrystals can also be obtained by photo and electron beam lithography5. Ion implantation is a prevalent doping method and compatible with very large scale integration (VLSI) but it involves lengthy and expensive doping process and has to be assisted by high temperature annealing6. The best known example of the lower dimensional silicon species, however, is highly porosified silicon made by wet etching which is a routine technique in semiconductor industry. Since the discovery of room temperature photoluminescence, porous silicon has been a subject of intensive research in an attempt to regain the dominance of silicon in microelectronics technology because it’s natural compatibility with micromachining process and optoelectronic integration. For all endeavours to improve the emission efficiency and stability of porous silicon, broad, dim and prone-to-bleaching photoluminescence emission from porous silicon have long been a constraint to device applications7. Despite the simplicity of fabrication, progress towards practical porous silicon devices has not been remarkable. Attempts were also made by doping silicon with active materials such as rare earth metal and transition metal ion so that radiative recombination is induced at impurity centres6, 8. Logically, a more promising host to these active materials is porous silicon for the fact that it has huge internal surface area resulting from a simple wet etching technique, suitable porosity and pore sizes for material ingression. More importantly, easily controllable porosity, pore size and thus specific surface area makes it possible to incorporate large variety of active materials into silicon. For example, organic dyes were impregnated into porous silicon and exhibit enhanced emission at 625nm9. Numerous of studies showed that by penetrating Er (III)8, 53

Tb (III)3+10 and Yb (III)11, 12 into porous silicon, efficient photoluminescence at 1.55μm was yielded at room temperature.

3.2 Light emission from microcavity devices

Along with all the efforts focused on the engineering the luminescent nature of low dimensional silicon itself, some other researchers are seeking ways to place active materials between mirrors so that a resulting optical microcavity can amplify light emission. Consideration of microcavity for light extraction is in part inspired by the established fact that microcavity is a routinely used tool to suppress undesirable spontaneous emission and endow emitted light directionality in III-V semiconductors industry. A typical example of such applications is vertical cavity surface emitting lasers (VCSEL) which features a planar optical microcavity embedded with gain materials. High reflective Bragg mirrors provide recirculated bouncing of light and amplification in the cavity. With more and more spontaneous emission coupled into the lasing mode, when the gain outstrips the loss of the cavity, net gain is achieved and lasing results. With a small change in cavity orientation compared to conventional edge emitting laser, threshold current in VCSEL is an order of magnitude lower than that in edge emitter and has a circular light beam contour. Control over spontaneous emission with microcavity is a major theme of cavity quantum electrodynamics (CQED). More generally, microcavity can provide significant enhancement for conventional light emitting devices (LEDs) which suffered from low efficiency and broadband emission. Organic light emitting devices (OLED) are a new technology in flat panel displays and light industry. OLEDs boast some benefits over liquid crystal displays such as wide viewing angle, high colour contrast, low energy consumption and high quantum efficiency (~100%). It is planar microcavities that revolutionise OLED by providing an environment of redistributed photon density of states, thus dramatically modify spontaneous emission from phosphors embedded in the cavities. In microcavity organic light emitting devices (MCOLED), luminescence from emitters is squeezed into an optical mode to escape out of the device as narrow band emission in predesigned colours and directionality. Primary colours (red, green and blue)13, 14 have been realised by embedding organic dyes into microcavities. Microcavity organic light emitting devices were initially constructed using transparent conductive metal mirrors and planar distributed Bragg reflectors. However, fabrication of distributed Bragg reflectors (DBR) has been complicated and expensive. Heavy loss from absorptive metals is a limitation 54 to improvement of emission efficiency. This drawback can be addressed by the use of all dielectric material reflectors, as has been shown in porous silicon which can be fabricated with great ease and at low cost.

3.2.1 Control emission with porous silicon microcavities

The effort to build up active devices based on silicon, a backbone material of microelectronics is continuing. One attractive option to realise efficient light emitting devices is to harvest and harness the emission from active materials by placing them into a favourable environment. The most effective way to control emission, as we mentioned in the previous sub-section, is to use photonic crystals are now readily achievable on silicon. In particular, compared with metal mirror based microcavities in MCOLED, lossless dielectric material based microresonators or microcavities are able to provide more effective and more predictable enhancement with tuneable optical windows and can exert strong modification on emission in the cavities. These hybrid structures have the potentialities to be tailored into a full range of light sources by incorporating active materials. It will be shown in this chapter that spectral narrowness, intensity enhancement, and spatial concentration of photoluminescence can be obtained in a quantum doped porous silicon microcavity.

Porous silicon’s suitability for photonic materials arises from their luminescent nature and more importantly from the flexibility and accuracy to harness the multilayer arrangement to meet our particular needs. Although microporous silicon exhibits efficient room temperature photoluminescence, it is not suitable for high quality multilayer structure formation. Only mesoporous silicon proves to be an ideal photonic crystal candidate because it is more likely in this morphological range to realise better layer phase interfaces, high porosity difference, and thus high refractive index contrast demanded for photonic crystals. Early studies majorly relied on monolithic porous silicon one dimensional microcavities with active media located in the central layer. Pellegrini et al15 fabricated porous silicon microcavities with photoluminescent central layer and observed enhanced and narrowed photoluminescence. Huge surface area of porous silicon and interconnected pores makes it possible for active materials to be conveyed into central layer in large amount. HA Lopez et al16 studied emission from Er (III) electromigrated into a porous silicon microcavity. Doping of microcavity resulted in an Er (III) emission enhancement factor of 38 while mission band was narrowed to

10nm. Modification of photoluminescence /electroluminescence was extended to include other luminant materials like organic dyes in microcavities. The study by Setzu et al17 demonstrated a simple approach to impregnatinging porous silicon microcavity by simple immersion of the structure in a solution of Rodamine 800 and showed dramatic modification of photoluminescence (an enhancement of 70). Similar approach was also taken by Canham et al18 to study the optical property modification of laser dyes impregnated in oxidized porous silicon. These techniques, however, bring about some undesirable side effects. For example, electromigration method suffered from indiscriminating and undesirable incorporation across the whole porous silicon structure that will lead to deleterious absorption by porous silicon at excitation region, reducing the capability of emission enhancement, i.e. Q-factor. High temperature annealing steps required to re-ordinate ions following incorporation will inevitably lead to oxidation of porous silicon, degrading the optical properties of microcavity by mode shift and cavity widening. To overcome the problem associated with post fabrication doping, Reece and co-workers19 used implantation technique to dope crystalline silicon with Er (III) and subsequently fabricated high Q-factor (1500) microcavity. As a consequence, emission at 1.55 μm was enhanced by 25 at resonance and narrowed to 3nm at low temperature (10K). However, complicated and expensive equipment to implement ion implantation limited its widespread application.

3.2.2 Incorporating quantum dots into microcavities

Limited success in lasing from organic dyes impregnated in microcavities is partly ascribed to tendency to bleach of these materials. At high concentration dye molecules in vicinity tend to form dimmers that suppress lasing transition so the dyes to be deposited in porous silicon structure are limited to low concentration. Molecular interaction with nano-structured silicon, as was found in the study by Latent et al9 also reduces the probability of population inversion required for lasing. Quantum dots are semiconductor nanocrystals in the dimensional range of 1-10 nm that exhibit characteristic optical properties with fluorescence emission being the most important. Emission wavelength of quantum dots is defined by the dot sizes. Compared with fluorescent organic dyes, quantum dots possess a higher extinction coefficient (10-100 times higher), narrower emission band (20-40 nm in FWHM, compared to 70-120 nm for dyes), superior resistance to photobleaching, photo and chemical stability. Unique core-shell structure of binary quantum dots exhibits tunable emission wavelength from 56

UV to near-infrared region, i.e.350-2500 nm by changing the dot size in synthesis. Quantum dots have exceptional brightness and can be imaged and measured with simple instrumentation. Quantum dots and/or their conjugates have been used in applications including labelling, imaging, and quantum dots lasing. High absorption cross section of quantum dots enables multicolour emissions from mixed populations of quantum dots by a single wavelength excitation source.

Introduction of a polymer coating covering quantum dots makes these conventionally hydrophobic nanosrystals more stable and soluble in aqueous solution. Functional groups of different types can be covalently attached to the polymer coating, endowing the quantum dots ability to be affiliated to various materials. Apart from functional groups such as carboxyl, thiol, amine, etc, biomolecules can also be attached to the polymer capping layer, opening up another avenue to quantum dot utilization through strong and specific bioconjugate reaction. Colloidal quantum dot suspensions have excellent transport properties, allowing dilution and compatible with low cost deposition techniques such as spin casting, phase separation, inject printing and micr- ocontact printing. Surface density of quantum dots is thus easily controllable. A number of attempts to incorporate colloidal quantum dots into various structures have been made including embedding quantum dots in polystyrene20 and poly (methylmethacrylate)21 microspheres and one dimensional microcavities22-26 .

Selectively incorporating quantum dots into microcavities could potentially meet the demand for low power multi-colour light emitting devices with high efficiency and high colour purity. Apart from the huge practical promise, incorporation of quantum dots into microcavities enables us to study quantum electrodynamics, a core issue of the photonics. Up to now, incorporation of quantum dots into a microcavity involves multistep fabrication of Bragg reflectors using vacuum sputtering27and vacuum thermal chemical-vapor deposition (CVD)28. Insertion of quantum dots into microcavities is performed through Molecular beam epitaxial (MBE) self-assembly method and in most cases as a part of microcavity fabrication process29, which limit the wider applications of quantum dots as an individual active material. It is highly appealing to develop new methods to fabricate microcavities in a simpler and more flexible way at lower costs.

3.3 Colloidal quantum dot doped porous silicon microcavities 57

We here describe a new way to incorporate II-VI colloidal quantum dots into one dimensional porous silicon microcavities. The technique involves modification of lifted- off porous silicon Bragg mirrors respectively with protein labelled with biomolecules that will conjugate with the functional groups attached onto the capping layer of on the colloidal quantum dots. The Bragg reflectors are designed such that the resonance wavelength of the assembled microcavity coincides with that of the quantum dots emission peak. The specific interaction biomolecules is the key in immobilizing quantum dots and bonding two separately fabricated Bragg reflectors to form a microcavity. The microcavity fabricated in this approach is illustrated in Figure 3.1.

Figure 3.1 Schematic illustration of hybrid microcavity fabricated by doping quantum dots between two porous silicon Bragg reflectors, both modified with biotinylated bovine serum albumin (biotin-BSA). One reflector (bottom mirror) is attached to the native silicon substrate while the top mirror is lifted off silicon substrate. Quantum dots streptavidin conjugates were immobilised on the bottom mirror through biological interaction between streptavidin and biotin which is attached to BSA. Central layer of the microcavity is constituted by two high porosity porous silicon layers where biotin-BSA is deposited.

3.3.1 Fabrication of porous silicon Bragg Reflectors

The microcavity proposed for this study will be an assembly of two identical porous silicon λ/4 Bragg reflectors containing 5 or 6 pairs of high and low porosity layers. λ is the designed resonance wavelength of the microcavity which determines the spectral position emission of quantum dots that will be modified. The two Bragg mirrors are designed in a way that two high porosity λ/4 layers jointly form a λ/2 spacer of the resultant microcavity. The function of high porosity centre is to allow easy admission of

58 biomolecules into high porosity pores for better immobilisation and subsequently better attachment of functional quantum dots.

The etched Bragg reflector is removed from the etching cell. Optionally, the porous silicon is soaked in pentane for a while before drying to reduce the mechanical stress during liquid-gas transition at surfaces. Pentane drying is not compulsory for structures fabricated in room temperature but imperative for those fabricated at low temperature.

3.3.2 Pre-modification of Bragg reflectors

The freshly fabricated porous silicon Brag reflector was left for 2-3 days in the air so that a mildly oxidized layer is formed on the surface. It was found that slightly oxidized surface is favourable for protein deposition.

Microcavities in this topic were assembled exploiting specific and strong biomolecular interaction between protein and the ligand. Binding between protein and ligand involves noncovalent interaction of the ligand with protein in some specific domains. Biotin is a soluble vitamin (H) with a molecular weight of 244.31. It is found to have strong binding tendency with avidin, a white egg protein or its bacterial form streptavidin. Both avidin and streptavidin have a molecular weight of 67000 and are tetramers which have four binding sites for biotin. Biotin-streptavidin binding has been identified as the strongest affinity ever known in biochemistry with a dissociation constant in the order of 4 ×10-14 M ( association constant of 1015 M-1), stronger than covalent bonding. Biotin-streptavidin pair is regarded as a typical model for studying protein-ligand interactions. A new avidin-biotin technology has been established on the strong, reliable and specific affinity between biotin and avidin or streptavidin in the last decade30. The technology takes advantage of the specific interaction between protein avidin (or streptavidin) and ligand biotin for the preparation of conjugates and complexes with immobilised biotin or avidin /streptavidin. Biotin-streptavidin technology has been exploited in bioanalytical chemistry, biotechnology research such as biosensor fabrication and diagnosis applications31. Biotinylation of antibody and other proteins is being actively developed in line with avidin-biotin technology32.

In this thesis, biotin was commercially available in the form of being covalently attached to BSA which is known to be spontaneously adsorbed to variety of surfaces and streptavidin comes as a conjugate with colloidal quantum dots. A schematic of colloidal quantum dot-streptavidin conjugate is shown in figure 3.2.

An aliquot of biotin labelled bovine serum albumin (biotin-BSA, Bought from Aldrich- Sigma. Diluted into 1mg/ml solution in PBS saline buffer solution, pH 7.4) was applied onto the Bragg reflector with a micropipette and left for 5 min at room temperature. Contact time should be maintained such that a densely packed layer of biotinylated BSA is attached onto the surface of porous silicon. High density of biotin-BSA in the central layer is an essential for high quantum dot deposition efficiency required for high light emission intensity. Excessive biotin-BSA was removed by pipette and rinsed off with high purity water (resistivity 18.MΩcm-2, produced by Mili-Q pure water system) and dried under a flow of high purity nitrogen gas. BSA is an elliptical molecule with a molecular mass of 65000 Da and a molecular size of 14 ×4 ×4 nm3. It has a stoke diameter of approximately 7 nm33, depending on the viscosity of the solvent. Although literature34 suggested that substantial adsorption of BSA happens in silica pores no

60 smaller that 45 nm, it is conceivable that some BSA will enter and deposit in pores which have an average size of 20 nm.

3.3.3 Assembly of hybrid microcavity via biomolecular affinity

Colloidal quantum dots (1 μM in 1M Betaine, 50 mM Borate buffer containing 0.005% sodium azide, pH 8.3) used in this study are commercially available (from Invitrogen Ltd). As is shown in figure 3.2, the quantum dots conjugate contains nanoscaled heterostructure with Cadmium Selenide (CdSe) as the core and Zinc Sulfide (ZnS) as the shell, covered by a polymer coating and conjugated with streptavidin molecules at the outmost surface. In this study, quantum dots with characteristic emission band centred at 565, 625 and 780 nm were chosen and diluted by a factor of 5 with the borate buffer solution provided together with quantum dots before use. Diluted quantum dots suspension was spot deposited on the biotin-BSA modified porous silicon Bragg reflector and left for 5 min before removal of excessive quantum dots by pipette and rinsing with water. The structure is dried in N2 gas flow. An inspection microscope was used to check the sample surfaces to ensure no visible precipitation or crystallisation of quantum dots occurred. Meanwhile, the top mirror which was etched and lifted off silicon was cut off at the rim and moved onto a piece of filter paper in ethanol. Free standing porous silicon was placed in a humid chamber and spotted with biotin-BSA solution mentioned above and left for 5 min. Finally, free-standing top mirror modified with biotin-BSA was reversed onto the Bragg reflector with quantum dot deposited to complete the assembly of the hybrid microcavity.

Porous silicon is a permeable material which is able to accommodate active materials in the porous film with large internal surface area. In particular, porous silicon multilayers with sharp porosity contrast as described in this thesis are well suited for incorporation of active materials of different sizes into the desired locations exclusively. Colloidal quantum dots, with an average size of 10-20 nm, can diffuse through the high porosity layer which has pore sizes of 30-50 nm while further diffusion is blocked by the low porosity layer annexed to this high porosity layer featured by pore size of less than 10 nm. As a result, quantum dots are concentrated in the high porosity layer meant to form the cavity layer. In this study, porous silicon structures are designed such that surface modification with biotinylated BSA and subsequent quantum dots deposition occur

61 solely on one high porosity layer of each component Bragg reflector, as is illustrated in figure 3.3.

Figure 3.3 Schematic illustration of quantum dots immobilisation via biomolecular interaction. Biotin-BSA is deposited on the high porosity layer of the bottom reflector, followed by quantum dot exposure. Biotin-BSA, having a molecular size of 14 ×4 ×4 nm3, is able to enter into high porosity layer with average pore size of approximately 20 nm but excluded by the low porosity layer. Biotin-BSA deposition and quantum dots immobilisation occur only in the high porosity layer.

The high porosity layer of the Bragg reflector infused with quantum dots will form the central layer of the assembled microcavity together with an identical layer from another Bragg reflector where biotinylated BSA is deposited as a complementary of streptavidin attached to quantum dot. A scanning electron microscopy (SEM) is as figure 3.4.

Figure 3.4 Cross-sectional scanning electron microscopy (SEM) image of a hybrid microcavity assembled from two Bragg reflectors. Distinct and smooth interfaces can be seen between layers and between two mirrors, indicative of effective bonding formed. Quantum dots are immobilised in high porosity layer and therefore at the very centre of the microcavity.

As can be seen from the SEM image, a very smooth interface is formed between two Bragg reflectors.

Figure 3.5 shows a photograph image of two samples under the same illumination conditions.

Figure 3.5 Visual comparison between monolithically grown (a) and assembled microcavities (b) fabricated with the same etching parameters for the individual layers. Comparability of 63 structures formed using two techniques are indicated by similar colours. Little ridges on the assembled structure were a result of imperfect assembly technique.

Sample a) is monolithically grown, whilst Sample b) is assembled through the biorecognition process. It can be seen that both samples exhibit the same mirror like qualities that are attributed to the high reflectivity band in the visible spectral region. Importantly no evidence of increased diffuse reflection is present. What is evident is that small cracks and/or ridges are present on sample surface of the assembled cavity: The author attributed these to imperfect mating of the top mirror with the bottom mirror over a macroscopic scale.

Inderect evidence that the dots are selectively doped in the cavity layer is provided by through a number of sources.. Firstly, quantum dot size information provided by the manufacturer shows that 5-10 streptavidin molecules are conjugated to each quantum dot nanocrystal with the size of is 15-20 nm. As a result of exclusion effect from the low porosity layer (pore size below 10 nm) immediately next to the high porosity layer, it is conceivable that the quantum dot streptavidin conjugates can only travel into and be immobilised in the high porosity layer (pore size 30-50 nm) of the Bragg reflectors, which is expected for a hybrid microcavity. Also, negligible change in reflectivity of Bragg reflectors upon application of quantum dots indicates that the absorption in the DBR is minor and hence number of dots in the mirror is small. Further physical characterization, such as EDS and TEM, would be useful in determining the details of the dot distributions. This would be good for further study which will aim for refined devices, but not necessary in this instance. No significant increase in the line-width of the cavity resonance was observed upon incorporation of the dots indicating that the absorption of the active material does not limit the finesse of the cavity.

3.4 Optical properties of quantum dot doped porous silicon microcavities

3.4.1 Specular reflectivity measurement

1-D microcavity is featured by a narrow transmission dip in a high reflection plateau defined by the periodic structure of component Bragg reflectors. The distinguished optical features of microcavities have seen many applications such as band pass filters,

64 optical modulators and resonators. The microcavities fabricated in the way discussed in the above section is characterised with both reflectivity and photoluminescence measurements. A typical reflectivity spectrum of the hybrid microcavity ensemble is shown in figure 3.6. A reflectivity spectrum of a monolithic porous silicon microcavity fabricated on the same etching conditions is also shown as a comparison.

Figure 3.6 Normal incidence reflectivity spectra of all-porous silicon and hybrid microcavity assembled from porous silicon Bragg reflectors.

Assembled microcavity has the same resonance wavelength position, comparable stop band width, line-width of cavity mode (6.5 nm for hybrid microcavity and 3.5 nm for monolithic microcavity, respectively) and therefore comparable Q-factor, indicating optical quality is not compromised in the biomolecular oriented assembly process. Slight widening of stop band suggests scattering loss at two interfaces around the central layer. Protein deposition and quantum dots embedding do not lead to change in physical thickness of the central layer. No significant increase in the line-width of the cavity resonance was observed upon incorporation of the dots, compared to an un-doped monolithically fabricated microcavity. This indicates that the absorption of the active material does not limit the finesse of the resonator mode, nor do defects introduced by the piece-wise fabrication process.

3.4.2 Photoluminescence 65

Photoluminescence is recorded at normal incidence.

Photoluminescence at low temperature is conducted on the sample mounted on a cryostat finger using conductive silver paste. The cryostat is evacuated to 1×10-5 Torr to maintain temperature ranging from 10K to 300K. A piece of flat silicon is treated in the same procedure as described in section 3.3.4 was used as a reference. Comparisons are also made with an identical Bragg mirror with quantum dot adsorbed in the same protocol.

3.4.2.1 Enhancement of photoluminescence

Spontaneous emission of an emitter can be modified by placing it in front of a mirror. A dielectric mirror can reflect and enhance the emission in front of it at certain direction in a wavelength range. Higher specific surface area of porous silicon means more biotinylated BSA and thus more quantum dots can be immobilised. Porous silicon Bragg reflectors can concentrate quantum dots as an emitter and alter the intensity of quantum dot emission through self interference between reflected and emitted photons. As we will see, photoluminescence of deposited quantum dots on porous silicon Bragg reflectors shows significant enhancement over the plane silicon loaded with quantum dots in the same procedure.

To achieve effective quantum dot deposition at the spacer, it is critical that biotinylated BSA is in contact with porous silicon so that a densely packed biotin-BSA monolayer is established. A comparison between different contact times of biotin-BSA with porous silicon showed that 5 min is sufficient for the monolayer formation. Longer incubation time of quantum dots allows more dots to be deposited on the biotinylated BSA functionalised surface. Impact of different contact time of quantum dot streptavidin conjugate with biotin-BSA modified porous silicon on the emission intensity is investigated and shown in figure 3.7.

Figure 3.7 Influence of incubation time of quantum dot conjugate on PL emission intensity. PL measurement were made on quantum dot deposited Bragg reflector (bottom mirror), excited by 514.5 nm Ar+ laser. PL intensity increases with longer incubation time but excessive long incubation corroded the bottom mirror and failed the microcavity.

As can be found in figure 3.7, longer exposure time leads to higher emission intensity because a larger population of quantum dots concentrated in the porous silicon is formed. Nonetheless, unnecessarily longer exposure to biotin-BSA and subsequent quantum dots suspension containing corrosive salt may corrode the unpassivated surface thus compromise the optical properties of the resultant device, indicated by convolution and blue shift of stop band in reflection spectra. A trade off between reasonable quantum dot immobilisation efficiency and structure integrity has to be reached. Visual inspection under microscope showed surface corrosion on samples after longer incubation times.

Deposition of protein on/in porous silicon is influenced by many factors, including porosity, pore morphology, pore size, pore size distribution and ion strength of the supporting medium. Surface hydrophilicity and protein charge play important roles in protein adsorption. Higher protein concentration leads to better deposition but saturates at certain concentration so in the present study, we used 1mg/ml concentration of biotinylated BSA in incubation solution, as suggested in literatures35, 36 for similar protein human serum albumin (HSA, molecular weight 66 kDa), which adsorbs on/in oxidized porous silicon and saturates at this concentration. Previous studies showed that hydrated hydrophilic surface is favourable for protein adsorption37. The dependence of emission intensities of quantum dots deposited on Bragg mirrors on the surface status is shown in figure 3.8.

Figure 3.8 Impact of surface chemistry on PL intensity of quantum dots on Bragg reflector. Freshly etched Bragg reflector (left panel) concentrated quantum dots and enhanced the peak intensity by 8 times whereas slightly oxidized surface (right panel) are more accessible to aqueous quantum dots suspension and therefore exhibited an enhancement of 28 times.

Higher extent of enhancement found on slightly oxidized porous silicon is thought to mainly result from hydrophilic surface which is more favourable for penetration of aqueous solution and thus protein attachment than that for hydrophobic surface freshly etched, though both protein and the oxidized porous silicon surface are negatively charged at pH7.4.

Stronger and more fundamental modification of photoluminescence of quantum dots inside the porous silicon microcavity, though, can be observed in a microcavity structure, as is shown in figure 3.9a. PL spectrum of the quantum dots embedded in microcavity shows characteristic features found on cavity modified spontaneous emission, i.e. a strong enhancement of emission on resonance wavelength 62.5 nm and strong suppression elsewhere in the stop band. In comparison with that deposited on acomponent Bragg reflector, an enhancement factor of 8.2 at peak intensity is observed. Based on the finesse and other physical parameters, emission enhancement of the microcavity in the context is expected to be approximately 40 times. This enhancement is primarily due to a spatial redistribution of the optical mode defined by the specific structure of the microcavity which prescribes a narrow light cone normal to the device surface. The discrepancy between the observed enhancement and what is expected is due to the difference of surface morphology of porous matrix and planar supporting silicon. As we have shown above, porous silicon can concentrate quantum dots and exhibits an enhancement of 9 times while 28 times of enhancement was found on oxidized porous silicon which provides more ideal surface conditions for such a concentration. The overall enhancement of 73.8 (9×8.2) is comparable with the predicted enhancement factor (40).

Figure 3.9 Photoluminescence enhancement and dependence of output emission on pumping power. a) Photoluminescence of quantum dots modified by the PSi microcavity (red line) compared with that of quantum dots deposited on a a Bragg reflector with the same procedure. Photoluminescence emission at 627.5 nm was measured amplified by a factor of 8.2, while FWHM was narrowed to 6.5 nm from 30 nm. b) Dependence of output emission collected from

69 microcavity on the excitation source input. Linear response across several orders of magnitude indicates fast radiative recombination time of quantum dots.

Power dependence measurement is an important aspect of photoluminescence characterisation as there are constant pursuits for the hope of lasing in LED development. Shown in figure 3.9b, by varying the excitation source power, wavelength peak value of output photoluminescence intensity exhibits a high degree of linearity over a several orders of magnitude. There is no sign of saturation at high pumping powers, which implies the limit of radiative e-hole combination in the system. The author attributes this to the fast recombination times in competition with non-radiative recombination, high spontaneous emission rate and low luminescence quenching of II- VI quantum dots. Nor is there sign of exponential evolution of emission intensity as on one hand, II-VI materials are intrinsically gaining materials, whereas on the other, microcavity structures in the topic provide quantum confinement in only one dimension. The resonant mode in a 1-D microcavity cannot be regarded as a lasing mode because there exist transverse leaky modes laterally which are not trivial38.

3.4.2.2 Spectral narrowness of the PL emission

Microcavity is often categorized as a band pass filter centered at the resonance wavelength. The spectral width of the emission that can transmit through the filter is determined by the finesse of the microcavity. Line-width of the emission spectrum of the above example is 6.5 nm, narrowed from the full width at half maximum of 30 nm for quantum dots deposited on silicon. Line-width of microcavity modified emission spectrum is defined by the quality factor of the microcavity. The reflectivity spectrum of microcavity for 625 nm quantum dots has a FWHM of 6.5 nm in transmission resonance that translates into a Q factor of 96.3. Confinement of emission in a narrow band means a high spectral purity which is a primary requirement in light source and display applications.

Similar results are also observed on microcavities doped with quantum dots with different emission band. Figure 3.9a shows the characterisation of a microcavity embedded with 780 nm quantum dots. As has been found, there exists significant lateral inhomogeneity across the surface of the sample, to simultaneously monitor photoluminescence and reflectivity on the same spot on the sample, a 440 nm Coherence Cube diode laser (with a power of 16 mW) is integrated into the reflectivity

70 measurement setup illustrated above so that the laser beam is focused onto the sample surface with a focus lens to create a light spot that overlaps the white light beam spot in reflectivity measurement. PL emission is directed and collected with optics of reflectivity measurement and acquired with Ocean Optics Suite software. Normal incident reflectivity measurement exhibited a high reflectivity band as wide as 300 nm from 665 nm to 965 nm. Simulation using Looenga effective medium approximation (EMA) model was conducted to determine the porosity and thickness of high and low porosity layers. Porosity and thickness values are estimated as 43.3% and 74.4 nm for low porosity layers, 80.5% and 145 nm for high porosity layers, respectively. Refractive index values for high and low porosity layers at the resonance wavelength were approximated as 2.39 and 1.43, respectively. The cavity mode was positioned at 799.5 nm with a line-width of 3.0 nm, giving a Q-factor of 267. High resolution PL spectrum of microcavity modified quantum emission, as is shown in figure 3.10b, exhibited narrowed emission peak centred at 799.5 nm with a line-width of 2.5 nm, in accordance with that of reflectivity data. Shown in figure 3.10c is the simulation of the reflectivity spectrum around the cavity. A good agreement with Lorentz model is obvious. Comparability with monolithically grown microcavity line-width of 2.38 nm, reported in ref39 in the same etching conditions indicates that the losses introduced by quantum doping and step-wise assembly technique proposed in this study is small relative to the overall losses due to scattering and absorption. High quality of the microcavity fabricated from porous silicon building blocks in a step-wise is similar to that formed from materials with less absorption such as Si rich SiO2 (SRSO) via sophisticated plasma assisted vacuum deposition technique in which a Q-factor of 82 was achieved at 825 nm27.

Figure 3.10 a) Measured (black line) reflectivity spectrum of mesoporous silicon hybrid microcavity synthesized from two six-period Bragg reflectors with 800 nm quantum dots embedded in between and its simulation (red line). b) High resolution spectrum of the PL emission band (solid triangles) from quantum doped microcavity and Gaussian fit (solid line). c) Measured reflectivity spectrum (solid squares) around the cavity mode of 799.5 nm and Lorentz fit (solid line).

Higher quality factor is achievable on microcavities prepared from Bragg reflectors fabricated at low temperatures. Figure 3.11 is the reflectivity spectrum and Lorentz fitting of a microcavity comprising of low temperature fabricated Bragg mirrors with 6 layer pairs.

Figure 3.11 a) Measured reflectivity spectrum of microcavity assembled from low temperature etched Bragg reflectors, doped with quantum dots. b) Measured reflectivity (solid line) around the cavity mode and Lorentz fit (dotted line). FWHM of the cavity mode at 771.05 nm was measured as 1.37 nm.

Low temperature fabrication yielded smoother interfaces between layers and between two Bragg mirrors, scattering losses induced by coherent scatteringat these interfaces was minimised. Inherent reflection caused by millimetre scale anisotropic fluctuation was also compensated for by small probing light beam size. As a result, line-width of the resonance mode is reduced to 1.37 nm which is equivalent to a Q-factor of 562, a dramatic improvement on room temperature etched structures. As is shown, line shape was well fitted to Lorentz model. Microcavities assembled from low temperature etched Bragg mirrors have a higher quality factor and therefore would give rise to a better enhancement and narrowness effects.

3.4.2.3 Spatial concentration of the PL emission by microcavities

In addition to measurement at the normal direction, PL emission is also observed from other angles in order to testify the ability of the microcavity to alter the spatial emission pattern. As schematized in figure3.12a, to measure angular resolved emission, in the revised setup described in 3.4.2, a collecting objective is mounted on a rotating stage precisely centered at the pump light beam spot on the microcavity surface. Pump laser (440 nm, 16mW) was coupled and focused onto the sample while emitted light was

73 focused with a focus lens mounted concentrically on the rotating stage and collected with the objective and acquired with Ocean Optics Suite software. Figure 3.12b shows the evolution of emission peak wavelength values (PWV) and peak intensities with the increased detecting angle. Accompanied with the blue shift of the PWV, line-with of the emission spectra widens from 3.6 nm at normal collecting to 23.4 nm at 30 degrees. Peak intensity experienced a decline with increased detection angle.

Figure 3.12 Directionality of microcavity modified PL emission. a) Schematic of PL angular dependence measurement setup. The focus lens and objective that collects the emitted light are mounted concentrically on a rotation stage equipped with a goniometer in regard to the beam spot on the sample surface. b) Measured angular dependent Pl emission spectra on increased collecting angle from normal to 28˚ with an increment of 4˚. The peak wavelength position shifts monotonically to the shorter wavelength, accompanied by peak broadening and intensity declining.

Both intensity enhancement and directionality achieved on a planar microcavity can be understood as a result of reduced optical mode density. It was predicted 40 that spatial distribution of the optical modes in a microcavity with one dimensional optical confinement is dictated by the spacing distance between two component mirrors. Furthermore, only one single mode is confined to a light cone around the cavity axis if the microcavity has a mirror separation of λ/2, as illustrated in figure 3.13. As the optical mode is redistributed both spectrally and spatially, light emission is confined in a light cone perpendicular.

Figure 3.13 Illustration of spatial radiation intensity distribution of a dipole position along the axis (z axis) of planar cavity of multiple λ mirror separation. Broadly distributed radiation pattern in free space becomes discrete and concentrated along the axis. Only λ/2 cavity gives one radiation pattern surrounding the cavity axis.

Spontaneous emission from an emitter embedded in the microcavity can only escape from the cavity through the only mode available. The emission pattern is also defined by the light cone. A mirror separation larger or smaller than λ/2 will lead to spread off of the confined emission and reduced emission intensity. While spontaneous emission pattern of condense active materials is spatially uniform like Labertian in free space, when embedded in a planar microcavity, maximal emission intensity can be viewed only at the direction perpendicular to the microcavity, as has been observed in the experiments. On the other hand, a 1-D photonic crystal differs from 3-D structure in that its band gap is strongly dependent on the propagation angle (incidence and collecting angle) of the wave relative to the photonic crystal surface. In a 1-D microcavity, if the incidence angle increase from 0 (normal incidence), resonance mode will move away from that at normal incidence and shift towards shorter wavelength direction as the Bragg reflection condition containing an incident angle other than normal can be satisfied only by a shorter wavelength, as indicated by the Bragg condition. With more energy being lost to increased in-plane wave vector k// so only higher energy wave can maintain the Bloch wave vector at normal which is the real component of wave propagation. As a consequence, microcavity modified PL emission will follow the spectrally changed mode in a trajectory towards shorter wavelength. For the same reason, emission peak will become wider as the optical mode at the oblique propagating angle in the layered structure becomes broader. However, peak intensities of the

emission become lower because of the shrinking wave vector. As suggested by some literatures, observed PWV in a microcavity is determined by 3.1:

ߣ௖௢௟௟ ൌߣ௖ ߠ௘௠ 3.1 Θem is emission angle of the cavity which is related to the effective refractive index of the cavity layer by 3.2: ଵ ߠ௘௠ ൌ ߠ௖௢௟௟ ͵Ǥʹ ௡೐೑೑

λc is the cavity mode position at normal collecting angle, λcoll is the emission

wavelength at collecting angle ߠ௖௢௟௟. neff is the effective refractive index of the cavity layer. Figure 3.14 indicates the agreement between observed and predicted PWV at detection angles from 1 to 30 degrees.

800 Observed PWV, nm 790 Predicted PWV, nm 780

770

760 PWV, nm PWV, 750

740

730 0 4 8 12 16 20 24 28 32 Collecting angle, ˚

Figure 3.14 Emission PWV evolution with collecting angle away from normal. A good agreement between measured (square) and predicted (solid line) using the model suggested by ref27 is obvious.

3.4.3 Tuneable light emission on porous silicon

Porous silicon is a versatile material whose geometry and dielectric constant can be tailored to a huge extent so that resonance wavelength of a microcavity may fall in a wide regime from visible to near IR. Another key advantage to the fabrication technique under discussion is that the light emitting material may be independently chosen with respect to the optical resonators. This allows the optical properties of porous silicon to 76 be optimised for applications in specific wavelength regions. In this study, we demonstrated quantum dot doped microcavities assembled to match the emission wavelengths of three quantum dots: 565 nm, 625 nm and 780 nm. Microcavities were assembled from 6-period Bragg reflectors designed for the respective wavelengths and accordingly etched at room temperature in the procedure described above. As is shown in Figure 3.15, microcavities doped with quantum dots with characteristic emission peaks at 565 nm, 625 nm and 780 nm exhibit similar optical properties in terms of PL enhancement and spectral emission narrowing behaviour. All measurements were referenced to with emission from quantum dots deposited on top of a Bragg reflector.

Figure 3.15 Photoluminescenc spectra from quantum dot doped porous silicon microcavities designed for 565, 625, and 780 nm quantum dots, compared with the quantum dots deposited on a Bragg reflector. Similar modification of PL is observed on three microcavities. Higher peak intensity from 565 nm microcavity can be attributed to stronger absorption of the quantum dots in at the excitation wavelength (440 nm).

Slight variations in emission intensities may be accounted for in consideration of the following factors: i) The different molar excitation coefficients of the quantum dots at their respective excitation wavelength; 77 ii) Different transmission properties of the porous silicon resonator at the cavity resonance due to increased intrinsic absorption of silicon with descending wavelength; and

Modified PL emission spectral line-widths centered at 565 nm and 625 nm are 6 nm and 6.5 nm, respectively, implying stronger material absorption in this region compared with 2.5 nm at 800 nm.

Intensity enhancement and unidirectionality are requirements for some applications such as backlight for liquid crystal displays where increases light emission is required in a certain direction. Introduction of colloidal quantum dots into microcavities opens up a new avenue to build up light sources with different emission wavelengths to cater for specific and manifold demands such as high brightness, monochromaticity and directionality with great simplicity and flexibility. Moreover, as we will show in this section, in situ tuning by introducing foreign materials into porous silicon to realise multiple wavelength emission in one single device is another merit specific to porous silicon and the technique we proposed is very suitable for tuning the output emission wavelength for both temporary and permanent purpose.

3.4.3.1 Tuning of microcavity resonances

Photonic crystals are a typical example that demonstrates effective control light through geometrical and spatial parameters: periodicity constant of the structure and propagation direction the wave. In addition to the material composition, incident angle and periodicity thickness of the 1-D multilayer photonic crystals are two critical conditions in studying the optical properties of this class of structure. The position of the stop band is governed by the layer thickness and the incident angle of probe wave. Even a change in the sequence of the component layers leads to the formation of quasi photonic crystal structure such as Thue-Morse sequence and Fibonacci sequence41. By doping the regular photonic crystals with defects, fundamental changes occur to the optical properties. It is the change in the thickness and sequence of one component layer that results in a 1-D microcavity.

3.4.3.2 Tuning of porous silicon microcavities

Thanks to the unique formation mechanism and ease of realisation, porous silicon offers more flexibility in designing and fabricating photonic crystals and quasi-crystal structures. By simply changing the fabrication parameters and/or parameter profile, photonic crystals with high geometric precision as well as quasi-periodic crystals have been demonstrated. In particular, structural tuning of porous silicon microcavity through varying anodisation current and thus the porosity of the central layer was reported by L.Pavesi et al42. PL emissions from luminescent central of porous silicon with different porosities were modified so that emissions with different wavelengths were observed. Modification of PL emissions from porous silicon central layer of varied thicknesses by a microcavity was also shown by Pellegrini et al43. By changing the thickness of the central layer of a microcavity, resonance wavelength change will shift and even the number of the resonances will change. A multimode microcavity can be formed by increasing the central layer thickness to the multiple λ/244. Change in the number of defects along the cavity axis results in the so-called coupled microcavities45. Mangaiyarkarasi46 et al demonstrated that controlled shift of the resonant wavelength of porous silicon microcavity, depending on the wafer type, can be realised by high- energy helium ion beam irradiation on the silicon wafer anterior to electrochemical etching. The irradiation reduced the carrier concentration, i.e. increased the resistivity of the locality of irradiation. As the proton beam can be focused on an area on sub- micrometer scale, high resolution features of porous silicon can be patterned. However, such a structural tuning of the optical properties involves fundamental of the structural design and fabrication. A more practicable way is post fabrication tuning by external intervention. Reece et al47 shown that by heating the structure from room temperature to 160ƷC in vacuum, resonance wavelength of the microcavity can be tuned in a range of 20 nm in a non permanent manner. Sharon M. Weiss et al. also reported thermal induced tuning of microcavity resonance wavelength by heating48. They concluded that resonance wavelength shifted to longer or shorter wavelength direction on heating, depending on the surface oxidation status.

3.4.3.3 In situ tuning of porous silicon microcavities

Anisotropic structure of porous silicon resulting from nano-scaled fabrication imparts sensitivity of the optical properties to the polarisation of the light. Tuning of the porous silicon microcavities is also possible by changing the polarisation of the probing light.

Jarkko J. Saarinen49, from Fauchet’s group, and Pavel K. Kashkarov et al50 showed that resonance wavelength of two polarisations differ and this difference increases with increased incident angle, suggesting the tuning mechanism of polarised light on top of well documented incident angle intervention, as discussed in the previous section. By infiltrating liquid crystal into the porous silicon, Fauchet’s group51 demonstrated that both reflectance and resonance wavelength can be tuned. Further tuning can be achieved by exerting an electrical field that modulate the mode position by controlling nematic orientation of the liquid crystals. However, tuning techniques conventionally used such as applying an electric field or heating is not convenient. Infiltration of light active materials such as liquid crystals into the pores exhibits low time response.

3.4.3.4 Tuning of porous silicon microcavity with external substances

However, the most effective way to tune the optical properties of a porous microcavity is to take advantage of its permeable morphology and surface chemistry potential. Therefore, tuneability of optical properties is a congenital benefit of porous silicon. Large and controllable surface of porous silicon imply that tuning of the optical properties of porous silicon can be realised in situ by simply introducing foreign substances into the porous network. Material admission into the porous matrix is a simple way to modulate the optical properties of the porous materials based on the fact that the effective refractive index that governs the optical properties of the complex is related to the composition of the medium. Presence or absence of materials can sensitively affect the optical properties of the porous materials. The unique responsivity of light behaviour in porous silicon to material ingress and removal has been utilised as a very important sensing mechanism to detect chemical and biological events as stimuli.

It would also be desirable that the light emission of LEDs can be tuned between wavelengths without fundamental changes in device design and fabrication. In this study, using the technique we proposed, the author fabricated a hybrid microcavity from two 6- period porous silicon Bragg reflectors. The structure is designed such that the assembled microcavity has a resonance wavelength at approximately 655 nm and is doped with quantum dots with 780 nm characteristic emission. Filling the porous silicon with glycerol aqueous solutions with variable effective refractive indices so that the spectrum of the microcavity including resonance wavelength, shifted to the region overlapping with the emission band of 780 nm quantum dots, PL emission of 780 nm

80 quantum dots was switched on in a modified way. The shifts induced by glycerol /water mixture varied from 86.89 nm to 108.2 nm, depending on the relative content of glycerol. The effective refractive indices of the glycerol / water are calculated by 3.3

௪ ௡ ା௪ ௡ ݊ ൌ ೈ ೈ ೒ ೒ 3.3 ௪ೈା௪೒

Where wW and wg are the weight fraction of water and glycerol respectively, nW and ng respectively denote the refractive indices of water (1.32896) and glycerol (1.46883) at 780 nm.

By varying glycerol content in the mixture which has an incremental refractive index with increased glycerol content, PL emission of the microcavity can be tuned continuously over a range of 20 nm. A microcavity centered at 663.5 nm, as is shown in figure 3.16a, suppresses the PL emission of 780 nm quantum dots embedded in the cavity. When glycerol mixture is infiltrated, cavity mode shifts to the region where it overlaps with quantum dot emission. PL is enhanced and narrowed. Fine tuning of the microcavity modified emission across the wide emission band of 780 nm quantum dot, i.e. from 749.07 nm for water and 770.38 nm for 60/40 glycerol/water mixture is shown in figure 3.16b.

Figure 3.16 a) Reflectivity spectrum of microcavity designed for tuning of PL emission, centered at 663.5 nm. b) Emission spectra tuned by infiltrating water and 60% glycerol aqueous solution, respectively. The microcavity emission may be tuned across the wide emission band of 780 nm quantum dots.

Resonance wavelength shift of microcavities is linearly depedent on the refractive index of the material filling the pores. The linear evolution of the emission PWV was observed in the hybrid microcavity, as can be seen in figure 3.17. Peak wavelength shifts were also modelled using matrix transfer method and the results are included in the figure 3.17, showing good agreement between measurements and the prediction.

Figure 3.16 Tuning response of the quantum dot doped microcavity. PL PWV shift changes linearly with increased glycerol content in the mixture. Measured (hollow triangle) results are in agreement with modelled trend (solid line) by matrix transfer method.

It was also observed that PL emission peaks become broader (FWHM 9.5-12.2 nm) after tuning in figure 3.16. This can be attributed to the reduced refractive index contrast between high and low porosity layers as the result of pore filling. As the quantum dots are isolated by the polymer capping, there is no interaction (energy transfer) between the quantum dots and the surrounding medium we observed no change in the intensity of the modified emission as the composition of the mixture varied. Tunability of and unattenuated cavity modified photoluminescence emission suggest the applicability of such structures in biosensing. Biosensing can be carried out by observing spectral shift induced by the binding of target molecules rather than amplitude change that has so far been hardly understood and unpredictable.

3.5 Conclusions and future work 82

I have proposed and demonstrated a new technique to incorporate quantum dots into porous silicon and build up functional structures. Incorporation of quantum dots was accomplished by functionalising the porous silicon surface with biomolecules so that quantum dots can be selectively immobilised on the desired surface in a predesigned way. Strong and specific interactions between the immobilised biomolecules and the function groups on the surface of colloidal quantum dots ensure that two porous silicon Bragg reflectors were tethered together to form a hybrid 1D microcavity.Quantum dots are exclusively confined in the central part of the microcavity. The resultant microcavities fabricated through biomolecular assisted assembly have a full width at half maximum of as small as 2.5 nm which equates to a Q-factor of 267 at 800 nm, better than what was achieved on the similar structures made from SRSO with more complicated fabrication technique. Higher quality (FWHM 1.37 nm) microcavities were built up from low temperature etched Bragg reflectors. The hybrid microcavities presented optical properties comparable with their monolithic counterparts. By embedding quantum dots into microcavities, photoluminescence emission of the quantum dots has been strongly modified, as we observed. Modification of the PL of quantum dots is consistent with cavity enhanced spontaneous emission, such as spectral narrowness, intensity enhancement and alteration of spatial emission pattern. Wide emission of the quantum dots was narrowed to below 3 nm. Strong enhancement of the emission implies high brightness, low power requirement and high energy efficiency. As is expected of a 1-D microcavity, modified PL emission was found to concentrate in a light cone as a result of strong directionality. Enhanced, spectrally and spatially concentrated emission of microcavities has the potential to become the basis of a new type of microcavity light emitting device. Optical devices based on porous matrix have an advantage that tuning of optical properties of the devices is easily achievable. By introducing glycerol /water mixture, we observed the switch on of 780 nm quantum dots emission modified by a microcavity where it was suppressed. Varying the composition of the glycerol content in the mixture, PL emission can be tuned in a range of 20 nm. Considering the wide operating wavelength of light sources required for full colour display (0.45-1.6 μm) and optical communications (1.3-1.5 μm), as well as the potential of microcavities for other photonic applications, flexible and predictable tuning of resonance wavelength has strong implications in light sources, modulators, switches and frequency converters etc, as a tuneable device can potentially serve as a number of devices featured by a single operating wavelength. It can be envisaged that by 83 introducing functional molecules into the device fabrication, a variety of active devices such as light emitters, modulators and light detectors can be created by purposeful device design and selective incorporation of active materials of interest. In addition, fabrication of such a hybrid microcavity opens up a new way to construct microcavities from a wider range of material source for spacers and underlies the establishment of a versatile technique to build up optical devices for expansive application purposes. Strong and specific interaction between biomolecules can also be exploited to assist aligning, guiding and facilitating precise positioning and assembly of miniaturised devices on one substrate thus accomplishing high degree of device integration while eliminating material incompatibility caused by multiple devices.

A more conceivable implication of this technique would be construction of microcavity biosensors that include a central layer constituted by preselected biomolecules. Photoluminescence based sensing on porous silicon has been plagued by broad, unstable and interference prone photoluminescence of this material. Photoluminescence based chemical and biosensing on porous silicon microcavities was highlighted by a number of milestone research works52, 53, but they were all on monolithic structures, limiting the accessibility of the active central layer which is confined to porous silicon made from lightly doped substrate for higher luminescence efficiency54. Photoluminescence emission modification of microcavities creates important benefits to implementation of photoluminescence-based porous silicon sensors. High emission intensity from the luminescent microcavities is readily detectable to naked eyes. Narrowed emission band allows for easy resolution of minor shift in emission wavelength. Bright and chromatic emission from microcavities can be exploited as a light source to probe interferometric sensors. Jason Dorvee and Michael J. Sailor55 demonstrated in their work that a low power LED was used as light source for a porous silicon Rugate filter sensor where the reflectance change was detected as a result of spectral shift off the peak maximum. Moreover, stable output emission and tunability of the microcavity containing efficient emitters such as colloidal quantum dots can be capitalized on as a sensor transduction mechanism. Sensing operation can be conducted by observing the target-induced spectral shift in photoluminescence emission which is far more unambiguous. Microcavities formed by assembly technique offer a direct access for target molecules to the most sensitive area of the microcavities which is otherwise buried deeply in monolithic structures. The central layer can be designed to selectively capture target

84 molecules of interest which approach it from side of the structure rather than travelling all the way through porous mirrors where the analytes are likely to be blocked and trapped before reaching the central stage. As the biological events occur at the centre of the microcavity, the highest extent of light-matter interaction and therefore highest sensitivity can be ensured. References

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Chapter 4 Bloch surface wave biosensors based on porous silicon multilayer structures In this chapter, a new type of label-free optical biosensor platform based on porous silicon photonic crystals is presented. The sensor is built on a porous silicon Bragg reflector by manipulating the thickness of the terminating layer. Such a structure allows the localisation of a surface mode at the interface demarcating the Bragg reflector and an adjacent. The spectral position of the surface mode is closely related to the refractive index and thickness of the terminating layer, which is more accessible to target analyte, compared to other resonant photonic multilayer sensors. Therefore, the structure can be utilized as a biosensor. This chapter will explain the design, fabrication, and testing of porous silicon-based Bloch surface wave biosensors and relate the sensor response to numerical simulations based on the transfer matrix method. Modification of surface chemistry of the porous silicon photonic structure via a hydrosilylation reaction enables passivation by a densely compacted organic molecular monolayer formed in hydrosilylation reaction. Further activation of the distal carboxylic group in the monolayer allows for anti-fouling species grafting and ultimately immobilisation of gelatin in the sensor as the bio-recognition element.The surface chemistry and sensor characterisation is monitored by reflectivity measurements and the results are quantified and compared with mathematical modelling. Successive surface modification processes trigger progressive red shift in Bloch mode. Some unique properties associated with structural and morphological design are discussed. These properties can potentially bring about benefits such as self referencing in sensing practices.

4.1 Optical biosensors

4.1.1 An overview on biosensors

By IUPAC’s definition1: “A biosensor is a self-contained integrated device which is capable of providing specific quantitative or semi-quantitative analytical information using a biological recognition element (biological receptor) which is in direct spatial contact with a transducer element. A biosensor should be clearly distinguished from a 88

bioanalytical system which requires additional processing steps, such as reagent addition.” A typical biosensor is composed of three main components: a biological (recognition) element, a transducer and a signal processer. The biorecognition element is a layer of a biological material that captures and interacts with the analytes of interest, incuring changes in physical, chemical or conformational properties or even conformation on the surface of biosensor. Perturbation (stimuli) caused by analyte binding and other interaction such as enzymatic digestion is detected and converted into electrical, thermal, gravitational and optical signals by the transducer. These signals are translated into a result recording by the electronic processing system. The three main components of a biosensor lie in different fields: receptors or detectors are mainly about biology; transduction is essentially a physical process whereas signal output including amplification and display are supported by the development of information technology. An illustrative schematic of biosensor configuration is shown in Figure 4.1.

Figure 4.1 Schematic diagram of biosensors. Sensing events occur on the transducer surface interfaced with biorecognition elements of various types. Changes on transducer surface are the apparent stimuli that can be detected and converted into a readable signal by electronics system.

Despite their commonality in detecting and monitoring aims, there are however, some distinguished advantages to biosensors over the bulk solution based instrumentation. As suggested by the definition, because the recognition processes occur at the surfaces of the transducers, biosensors detect the presence of target molecules at a surface. The results obtained on biosensors hold more relevance to the biological activities than that monitored in solution, because the vast majority of biological interaction activities occur at surfaces, nominally solid/liquid interfaces, such as membranes and the gel-like extracellular matrix (ECM), as has been found in biological investigations2. Surface

based interaction also has the potential to enhance the detection sensitivity, as has been seen in surface enhanced Raman spectroscopy (SERS)3, 4. To achieve accurate and specific detection, sensor surfaces must have the ability to pick up the target analytes of interest in a discriminatory manner. Selectivity of the transducer is imparted from exceptionally selective binding capability of biological molecules with other molecules, biological or not. Therefore, the interface between biorecognition units and transducer is critical to the robustness and performance of biosensors. The surface of the transducer of all biosensors has to be modified to acquire the capability of selectively binding the target; on the other hand, transducer surfaces have to be made inert to physiological and other relatively aggressive matrices with which sensors areexposed to. Non-specific adsorption of analyte and interfering molecules are frequently circumvented using judicious surface chemistry. Thanks to the contribution from chemists, numerous surface chemistry schemes have been established to immobilise biorecognition element to transducer, including physical adsorption, covalent and affinity bonding.

4.1.2 Optical Biosensors

The applicability of optical transduction in biosensing is that biological molecules have intrinsic optical properties including absorption, luminescence, scattering and refractive index that are different to their surrounding environment. Optical biosensors exploit the change in optical properties of interface containing biorecognition elements caused the interaction of the interface with the target molecules. Optical transducers are materials or devices with distinct optical properties sensitively responsive to the environment. Changes in the properties at the surface are detected by the transducer and converted into measurable optical signals. Optical properties that have been exploited for sensing signal transduction include chemi-luminescence, fluorescence, absorbance, reflection, light scattering and refractive index. Compared with other transduction techniques, optical sensors enjoy numerous benefits including:

1) Less electromagnetic interferences that are common in electrochemical sensors;

2) Fast response, signal/noise ratio;

3) In many configurations used for optical detection where techniques such as luminescence, Raman scattering or reflectivity are used, as it is the case in this thesis, no need for labelling of bio-recognition molecules or target;

4) Possibility of non-contact, non-invasive, non-destructive and telemetric measurement;

5) Amenable to multiplexing and scaling for lab-o-a-chip approaches;

6) Potential for integration with optoelectronics devices for micrototal analysis system (referred to as μTas).

Optical biosensors are routinely used in biomolecular interaction studies thanks to their ability to reveal detailed information about molecular affinity and binding kinetics, thus making up a class of sensor family: affinity biosensors. There are two major detection modes prevailing in optical biosensors: direct detection and indirect detection. Usually, fluorescent or radioactive tags or labels and second reporters (such as an epitope or antibody that can initiate an enzyme reaction and ultimately resulting in colour change) are required in indirect biosensors. Despite the high sensitivity, labelled methods are giving way to label-free mode due to some parasitic drawbacks or even insurmountable hurdles. Labelling is time consuming and labour extensive. Labelling process inevitably alters surface nature, conformation and activities of the host molecules and lead to uncertainty in detection experiment. The reliability of labelled methods is undermined by inaccessibility of labelling sites, steric hindrance, and unavailability of labels with equivalent label capability for different molecules. In contrast to indirect labelled method, label-free sensors eliminate experimental uncertainties from fluorescence quenching, shelf life and fluorescence background because label-free sensors exclusively detect surface events or resonance, which is induced by surface binding. Therefore, label free methods have the potential for lower background signal. For some applications such as detection of explosives, nonelectrical optical transduction offer critical advantages.

Performance enhancement of biosensors mainly involves transducer surface area increase (transducer design and fabrication) and , electromagnetic field localization, i.e. optical resonance (optical properties) or enhancement of electron transfer efficiency (electrochemistry properties). As will be seen, surface area enhancement and EM field

localization can be accomplished by innovative transducer design and fabrication such that on one hand, large surface is provided for immobilization of bio-recognition molecules and targets, on the other hand structural design enables EM resonance, in particular in optical regime, as in the case of mesoporous porous silicon.

4.2 Label-free optical biosensors

Although labelling is not needed in sensing methods such as quartz crystal microbalance (QCM), piezoelectric, and thermal transduction techniques, label-free detection are literally referred to as optical techniques. On the other hand, spectrophotometry and spectroscopy can hardly be regarded as an optical biosensor as they are based on detection of bulk material.

4.2.1 Evanescent wave as a sensing platform

Evanescent waves are standing waves exponentially decaying with the distance from the boundary between two media of different dielectric constants. In essence, an evanescent wave is a decaying guided light outside the waveguide. Evanescent waves are usually excited through total internal reflection (TIR) or attenuated total reflection (ATR). As the Maxwell’s equation requires both electromagnetic field continuity and energy conservation, there has to be some imaginary part of light transmitted through the boundary. However, this part of light cannot exist unless as evanescent waves. Optical biosensors detect the binding induced change in resonance on the surface of the transducer. The resonance between the incident light and the evanescent waves is determined by the incident angle, wavelength, and polarisation of incident light, and the refractive indices of medium on both sides of the boundary. Generally binding events are detected as changes (shifts) in resonant angle, wavelength or other optical properties as these events induce refractive index and /or physical thickness change at the interface. An illustration of label-free optical biosensor configuration is shown in figure 4.25.

Figure 4.2 Schematic diagram of label-free optical biosensors relying on measurement of bulk refractive index of the analyte solution by evanescent wave. Figure reprint from ref [5].

In the past decades, the majority of the effort towards label-free biosensors was focused on evanescent wave based techniques, exemplified by Surface Plasmon Resonance (SPR) sensors.

4.2.1.1 Surface Plasmon resonance (SPR) biosensors

A surface plasmon is a collective oscillation of free electrons at the interface of a metal and a dielectric medium which can penetrate 50 -200 nm into the dielectric material at the metallic surface. SPR is prevalently excited using a high refractive index prism on which a metallic thin film (gold or silver) is deposited. Biorecognition elements are immobilised on the metal surface and are open to the analytes. Light is coupled into and resonates via SP modes at the metal-solution interface. The resonance ofSP oscillation appears as a minimum in the intensity of reflected lightas the light coupling to those modes dissipates via thermal process (e.g. resistive heating). Biological binding and /or other events capable of causing a refractive index change at the surface are transduced as a change in resonant angle, wavelength, intensity (amplitude) or phase in reflected light as is illustrated in figure 4.3.

Figure 4.3 Diagrams of surface plasmon resonance sensors. a) SPR based on Krestchmann prism configuration6. Other light coupling geometries used for SPR excitation include planar waveguide (b)7 and optical fibre (c)8.. SPR can also be launched by multiple diffraction on low cost gratings (d)9are being used to overcome the drawback associated with bulky prism. Signal output of SPR can be resonance angle, resonance wavelength (d) or intensity (amplitude).

Since its introduction into sensing applications10, SPR has become a dominant affinity based immunosensor and powerful tool in studying interactions between biomolecules in biological research. SPR allows specific, sensitive and rapid determination of interaction model, specificity, kinetic rates, thermodynamic and equilibrium constants. For all the merits of SPR such as amenability to automation, there are obvious benefits to find alternatives to SPR which is limited by some inherent shortcomings. On the other hand,being inspired by SPR, a range of evanescent wave based optical techniques have come into event. .

4.2.1.2 Evanescent waves at dielectric interfaces

In principle, better sensitivity can be achieved with SPR using waveguide technology including optical fibre and planar waveguide so that light in the waveguide undergoes a multiple round trip in a confined space, ensuring multiple light-matter interaction. In addition, metal coated grating coupling is another low cost alternative to excite SPR. Moreover, evanescent generated on these dielectric devices are utilised for biosensing. A variety of sensing schemes based on dielectric materials have been demonstrated. Examples of these new schemes are waveguides11, optical fibres8 and resonant mirrors12 . In a resonant mirror, not only refractive index but physical thickness is measured as well.

4.3 Photonic crystal-based biosensors

The ability of photonic crystals to control, reflect, trap, slow, guide light has been utilised widely in optics and optoelectronics to build up mirrors, filters, resonators, waveguides, modulators and photodetectors. Well defined reflection or transmission features of photonic crystals are especially suitable for sensor applications because these features are sensitive to the minor change in the surface landscape at nanometre level (structural sensitivity) and the environment of the photonic crystals (environment sensitivity). Mass adsorption /elimination at the surface of a photonic crystal will lead to significant change in spectral, spatial, intensity or phase of the electromagnetic wave illuminated on it in a way different from that without adsorption/elimination (original status). As a consequence, compared with original status, a shift in spectral features such as peak wavelength value (PWV), reflected light angle, intensity, polarisation or wave phase is observed. The extent of such shift is exploited as a measure of the amount of material present / removed from the surface of photonic crystal. A detectable optical property change of the photonic crystals means the targets do not need to be tagged to be seen. An advantage of the photonic crystals is, the opportunity to create a defect in the perfectly periodic structure so that a resonant condition is established. A beneficial consequence of the defect is a distinguishable feature appears in reflectivity or transmission spectra such that minor changes in these features are discernible. Under resonant conditions, light is localised around the defect and strengthens interaction between light and materials.

Although biosensing has been conceptually demonstrated in photonic crystals with 2 or more dimensional periodicity modulation13-15, 1-D structures are more widely used as biosensing platform16-19, 1-D air-hole arrays, slabs and 1-D gratings are typical 1-D photonic crystal but 1-D photonic crystals are mostly understood as multilayer thin film structures, namely Distributed Bragg reflectors. In particular, individual layers in a multilayered ensemble can be comprised of nanometric materials in sizes so small relative to light wavelength that a layer with a distinct amorphous ratio appears to be a homogeneous entity to light. Those quasi-multilayered structures containing mesoporous components, as introduced in chapter 1, constitute a class of mesoporous multilayer photonic crystals. The prominent advantage to biosensors based on photonic crystals made up with porous materials is that the porous matrix provides huge internal surface for captor immobilisation and analyte capture, thus yielding higher sensitivity over the same structure consisting of plane layers. The author has pointed out in chapter 1 that mesoporous multilayer photonic crystals are best incarnated in porous silicon. Tremendous research work has been devoted to biosensor applications based on porous silicon as a photonic crystal. Biosensors in various geometries on porous silicon have been demonstrated including 1-D microcavities20, 21, Rugate filters22, 23, waveguides24 and resonant mirrors12.

4.4 Porous silicon multilayers for Bloch wave localization

4.4.1 Bloch waves in 1-D photonic crystals

Following the discovery of Bloch surface waves at the surfaces of photonic crystals25, it was soon theoretically and experimentally demonstrated that surface waves can exist in semi-infinite or finite 1-D multilayer structures if some conditions are satisfied such as arbitrary termination and total internal reflection26-29. Surface waves are localized optical field and can exist inside the forbidden band gap of 1-D photonic crystals30. Bloch surface waves are nonradiative and characterised by an exponentially decaying optical field in the perpendicular direction on either side of the dielectric-periodic structure interface, and in this way they are analogous to surface plasmon polariton (SPP)31. As the propagation of light in a periodic medium is described by Bloch wave;

optical problem of surface states is often solved by analytical Bloch mode approach32, a resonance at the boundary of such medium is usually referred to as Bloch surface mode. Figure 4.4 illustrates optical field intensity profile in a multilayer structure33.

Figure 4.4 Illustrated field intensity profiles as a function of depth in a multilayer dielectric photonic crystal with an interface to air. The surface mode exists in the first layer. The graph reprinted from ref [33].

The similarity between BSW and SPP is only limited to the fact that they are launched via prism coupling which enables total internal reflection at the surface exposed to the third dielectric medium, i.e. through Kretschmann configuration. BSW is supported between two dielectric media rather than a metallic film which is absorptive in optical region, making it possible to produce high finesse modes. Low loss also means high amplitude and longer decay distance of localised field because there is no leaky mode. Unlike SPR which is exclusive to TM polarisation, BSW can be excited by either TE (s) or TM (p) polarised light because it is excited at the boundary of dielectric media34. The structural peculiarity of truncated photonic crystals can be utilised in label-free optical biosensing because the characteristic frequency of the surface Bloch mode is determined by the thickness and surface properties of top layer of the photonic crystal35, 36. 97

Because of their evanescent property, Bloch waves are not extended to the surrounding medium and cannot be collected in straightway as that used in photoluminescence measurement. Similar to SPR, BSW is usually observed as a loss in reflected light and appears in angular or wavelength dependent reflectivity spectra. Other observation mode including phase and intensity (amplitude) are also applicable.

31 Shinn and co-workers proposed sensor applications of Bloch surface waves on TiO2-

SiO2 alternating multilayer. Accumulative layers of cryolite on the surface yielded successive shift of resonant angle. In another work, Villa et al 37 investigated wavelength dependent response of surface mode to the changes in thickness and absorption & transmission properties.

38 Using TiO2-Ta2O5 multilayer, Konopsky and Alieva demonstrated that by forming a monolayer of streptavidin on the surface of the top layer of a TiO2 (SiO2-TiO2)3 structure, a signal-to-noise ratio of 15 and lowest detection limit (LDL) of 20 fg biotin. Guo et al39 demonstrated the real-time monitoring of biomolecular binding on similar configuration containing TiO2-SiO2 alternating layers. However, in these systems, complicated techniques were needed in sensors fabrication. Sensing applications suggest surface morphology and surface chemistry should be favourable for both biorecognition element immobilisation and analyte capture are desirable. In a more recent work, Giorgis et al. showed that Bloch surface waves supported by silicon nitride films are able to detect refractive index changes as small as 3.8×10-6, corresponding to a sensitivity of 1.5×103 nm/RIU. This is a higher sensitivity than that of SPR in visible region40.

4.4.2 Spatial optical confinement across porous silicon for biosensing

Optimisation of optical sensor sensitivity is closely related to fortified light-matter interaction strength by increasing the amount of light through resonance so that repeated and longer interaction with material would result in enhancement of signal provided that light is localized in the area where material admissions or removals take place. However, this idealism is not always readily attainable. Multilayer photonic crystals made from plane films are hardly useful in biosensing applications as they do not afford suitable surfaces to accommodate either receptors or analytes. High quality 1-D porous silicon microcavities suffer from analyte infiltration blockage by small pores (<10 nm) in 98

numerous layer pairs with high porosity contrast required for high Q-factor. As a result, an embedded cavity where the enhanced optical field is confined is hardly accessible to the analyte. This restricts the degree of porosity modulation and consequently overall finesse of the resonance mode available for sensing. Attempts to compensate for this limitation using structures with smaller porosity contrast and larger pore size in the mirror lead to enhanced scattering losses, broader spectral features and increased mirror thickness. Porous silicon Rugate filters are another important biosensor candidate. To achieve pronounced reflection feature, Rugate filters usually have a large number of layers which impose significant restrictions to analyte diffusion. It is therefore highly desirable to have a sensor design that enables extension of electromagnetic field confinement from the interior of the photonic crystal to the region biological molecules are bound while exploiting the morphological benefit of porous network and structural properties as a multilayer photonic crystal. Such an extension of optical confinement for sensing has been realised in multilayer photonic crystals, as was introduced in 4.5.1. In the context of photonic crystals, an irregular layer or an incomplete layer in a periodic multilayered thin film stack are regarded as a defect and such a defect will attract optical confinement around it. Figure 4.5 shows a comparison of field intensity profile of a multilayer microcavity41 and a multilayer one dimensional photonic crystal42 harnessed to support total internal reflection at the outmost layer.

Figure 4.5 Field intensity profiles in a microcavity containing two multilayer Bragg reflectors (a) (adapted from ref [41]) and a structurally modified Bragg reflector (b) (adapted from ref [42]). In a microcavity, the field is confined around the central layer so the strongest field 99

intensity is enclosed inside the structure and less accessible to the analyte. The field intensity reaches maximum in the last layer in a Bragg reflector if a defect is created in that layer.

Flexible tuning of spatial location of the “defect” in a porous silicon Bragg stack by simply varying the etching parameters will enable selective enhancement of optical field and facilitation of interaction between the probing light and analyte at the right region.

4.4.3 Surface waves biosensors on porous silicon

Surface waves have recently been successfully realised in porous silicon multilayer photonic crystal structures43, 44 and demonstrated potential for sensing applications45, 46. However, the most significant advantage afforded by these structures built on porous silicon is that the concentrated optical mode located adjacent to the ambient medium is suitable for sensing large macromolecules such as proteins and DNA. Porous silicon not only serves as a physical support for Bloch mode, it also provides accommodation for biomolecular recognition events. As has been manifested, BSW is in essence a guided wave. Its amplitude maximum is in the final layer rather than at the interface between the final layer and the surrounding medium. Coincidence of Bloch mode maximum and molecule adsorption or binding in porous silicon optimises the overlap of surface mode and target analytes. With light confinement extended to the area where binding events occur, BSW sensors can principally overcome some of the challenges associated with structures with embedded field confinement (microcavities) or restricted by mass diffusion (microcavities and Rugate filters).

4.5 Bloch Surface Wave biosensor Fabrication

4.5.1 Structure design

The Bloch surface wave sensor used in this study is based on a periodic multilayered porous silicon Bragg reflector with an irregular outmost layer. This extraordinary layer presents as a defect that attracts field confinement around it. As the layer is at the top of the multilayered structure, optical localisation is brought to the region and exposed to the biological interaction events. As has been demonstrated in the previous chapter, large porosity, i.e. refractive index modulation capability in porous silicon multilayers has been engineered to produce a full range of optical and photonic crystals including

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broad reflection dielectric laser mirror47, high quality factor (up to 7300) microcavities48, and Rugate filters49. Microcavities are especially noticeable in biosensor implementation in that these structures present sharp resonance band which are able to resolve minor changes which are otherwise undiscernible. On the other hand, porosity can be so finely modulated such that one can obtain a continuous refractive index profile for structures like Rugate filters, which, up to date, remains difficult to realise. It is therefore conceivable that one can obtain porous silicon structures with any desired layer arrangements and sequence in a straightforward way while maintaining the desirable porosity contrast.

The optical Bloch surface wave sensor in the topic is etched as a monolithic structure from highly boron-doped silicon wafer described in chapter 2. The etching sequence used to fabricate the Bloch surface wave structures is A (LH) 4 where A represents the irregular layer on top of a Bragg reflector containing 4 pairs of alternating low and high porosity layers, symbolised by L and H. It is constituted of a Bragg reflector with alternate high porosity (low refractive index) and low porosity (high refractive index) layers. This sequence is chosen to produce a broad reflection band in the near infrared spectral region for light incident at 45 degrees through a prism coupler. The spectral region was chosen to correspond to the high sensitivity range of spectroscopy equipment used in sensing studies. The etching time of the top high porosity layer is increased by a factor of 1.3 compared with that in the bulk Bragg reflector in order to position the surface mode near the centre of the high reflectivity band.

4.5.2 Sensor fabrication

Based on the correlation between the applied current and the porosity modelled from EMA method, the Bloch surface wave sensor was fabricated from highly boron-doped silicon wafer using 25 % hydrofluoric acid as the electrolyte. A current train of A (LH) 4 was applied through a computer-controlled programme. The guideline value of A, L and H are listed in chapter 2 (2.2.1.2), but varied due to current drifts and subject to adjustment. The porous silicon dielectric film is lifted off the native silicon substrate by applying a high current pulse in 15 % HF ethanolic solution.

4.6 Characterisation of BSW structure

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4.6.1 Spectral reflectivity measurement

Figure 4.6 shows the experimental measured reflectivity spectrum of a freshly etched porous silicon Bloch surface wave structure in the visible region. Thanks to the ease of control over the layer thickness, the surface mode can be engineered from visible through to the IR region in the electromagnetic spectrum.

The Bloch surface mode appears as a dip in a reflectivity spectrum as the probing light hitting the interface is lost to the Bloch evanescent wave at the frequency defined by the structural and geometrical nature of the sensor. The resonance at 632 nm corresponds to the surface wave mode, which arises when the incident light is coupled by frustrated total internal reflection through the truncated Bragg reflector. The spectral band (489– 807 nm) in the region around the surface wave mode indicates the reflectivity stop band of the dielectric mirror. Light incident on the PSi films will experience strong Bragg reflection at these wavelengths. The reflectivity dips at the band edges of the stop-band relate to increased absorption/scattering within the films due to Brillouin-scattering type slow light modes. At the longer wavelengths the light is reflected at the PSi / air interface by total internal reflection and reflectivity is close to 100%. At shorter wavelengths the incident light is absorbed strongly by the silicon component of the porous silicon films and the reflectivity is modified accordingly. Importantly, if the multilayer structure exhibited very low scattering/absorption losses, light coupled into the band-edge and Bloch surface modes would be out-coupled in the same direction as the reflected light and this would reduce the amplitude of the band-edge resonance dips observed in reflectivity. This means that the intrinsic losses in the porous silicon films aid in resolving the spectral positions of the different modes in the photonic structure. The importance of the TE polarization is understood when considering Fresnel reflection of each of the dielectric interfaces at non-normal incidence. For TE polarization the reflectivity increases monotonically with increasing angle of incidence, whilst TM polarized light the reflectivity decreases toward zero at Brewster’s angle. This results in a TM reflectivity band with a smaller spectral width and lower absolute reflectivity, which are unsuitable for launching surface modes.

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Figure 4.6 Reflectivity spectrum of a newly etched Bloch surface wave sensor. Surface mode appears at 632 nm with a FWHM of 15 nm, comparable with that of Rugate filters but structure with open space is much simpler and amenable to analyte capture as a sensor.

Scanning electron microscopy (SEM) images of a Bloch surface wave structure in figure 4.7 show uniform distributed mesopores in the top layer (a) and distinct layer interfaces (b).

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Figure 4.7 Scanning electron microscopy images of a Bloch surface structure containing a 4 period Bragg reflector and an irregular layer. a) Top view image; b) cross sectional image. The irregular layer is at the bottom of the mirror. High porosity layer is in dark gray while low porosity layer is in light gray. Dotted scale bars give an indication of pore size and layer thicknesses.

4.6.2 Numerical modelling of surface mode

Simulation and modelling of electromagnetic behaviour in composite media with components’ sizes in the order of light wavelength has become a powerful tool in feasibility study, optical feature prediction and design optimisation before fabrication of nanoscaled optical devices. It also proves to be useful in verifying the fabricated devices.

All numerical methods available for modelling propagating behaviour of light involve solving Maxwell’s equations that govern the behaviours of light as electromagnetic wave in all space and time. When the boundary between materials is involved, incident direction of light and orientation of electromagnetic wave are taken into consideration, Maxwell’s equation can be simplified and some numerical models can be derived. A typical simplified method is transfer matrix method (TMM) which can be employed to describe behaviours of light such as transmission and reflection in multiayered films like PSi. As was discussed previously, effective refractive index of each of the multilayers can be estimated using an effective medium approximation (EMA) method, taking into account the relative fraction of crystalline silicon and voids in each layer. To deal with the effect of chemicals introduced in surface modification and subsequent

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sensing processes, a multi-component Bruggeman approximation model50 is incorporated into the simulation method to predict and verify the evolution of the optical mode. A good agreement between experimental measurement (solid line) and numerical modelling (dotted) is demonstrated in figure 4.8(a). Marked discrepancy in FWHM and depth between simulation and experiment can be attributed to scattering at multiple layer interfaces and lossy absorption of silicon. In ref46, Descrovi et al showed a surface mode with a FWHM of 6.5 nm in IR regime ( 1530 nm) in porous silicon.

Figure 4.8 (a) experimentally measured (solid) and simulated (dotted) reflectivity spectrum for a freshly etched porous silicon optical Bloch surface wave sensor. Important features include the surface wave mode (631 nm), and the two band-edge modes (489 and 807 nm). (b) Refractive index profile of the surface wave structure at the surface wave mode coupling wavelength. The distance is measured relative to the interface between the prism and the multilayered film. Field intensity profiles for wavelengths corresponding to the band-edge modes and the surface wave mode are shown in (c) and (d), respectively.

From the simulation it was determined that in the bulk Bragg reflector, the high refractive index layer has a porosity of 44% and a thickness of 71 nm and the the high

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porosity layer has a porosity of 75% and a thickness of 129.5nm. The top high porosity layer is 1.3 times the thickness of the other layer and is the main factor affecting the mode position of BSW mode. The Bloch surface mode supported by the structure is at 632 nm while band-edge mode is at 489 nm. Close correlation between top layer thickness and mode position is usually used to tune the position of the surface wave mode relative to the band edge. From the layer sequence and their refractive index profile (illustrated in figure 4.8 (b)) and optical measurement, field distribution in the underlying structure is calculated and shown in figure 4.8 (c) and 4.8 (d). A field intensity maximum appears at 631 nm and exponentially decays in both directions away from the top layer interface. This indicates that the Bloch mode position is associated with the optical properties of the top layer whereas in the bulk structure, oscillation does not have significant influence on the overall field intensity in the top layer and therefore have limited contribution to the Bloch mode position. Different contributions from the bulk structure and the top layer can be exploited as a self reference to rule out nonspecific and irrelevant events occurring in layers other than the top layer where biological recognition is confined as designed. A small discrepancy between the simulated and measured positions of the long wavelength band-edge position is observed in figure 4.8 (a) due to interface scattering, absorption and layer aging.

A major difference of BSW from SPR is that unlike SPR which is travelling at the very surface of a metallic film, BSW exist in the top layer, in the vicinity of the surface. Therefore, Bloch mode is more of a mode guided by the first layer than a genuine surface mode like SPR33, 51. Such a conceptual inaccuracy, however, turns out to be a merit rather than a shortcoming in specific material like porous silicon. In porous silicon Bloch surface wave structure, a high porosity layer acts as the boundary which sits at the maximum of the optical field rather than at the exponential decay area or even decay tail. Since surface processes especially sensing events are confined in this layer, optical-matter interaction can be ensured to the highest extent.

4.6.3 Effect of terminal layer thickness

While the spatial light localisation is determined by layer sequence, the spectral position of the localised mode depends on thickness, refractive index and absorption of the layer the mode is located. The dependence of the surface mode wavelength resolved

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reflectivity spectrum on etching time for the top layer is shown in figure 4.9. Similar results were also reported in ref51.

Figure 4.9 Dependence of spectral position of surface wave on the thickness (represented by etching time) of the top layer of porous silicon. Etching times for the bulk Bragg reflector are kept consistent for three samples. Mode line widths are 18, 18 and 17.5 nm, respectively while reflectivity dip becomes deeper towards longer wavelength.

As has been mentioned, it is the thickness and surface properties of the last layer of photonic crystal that is critical in determining the properties of the Bloch mode. A regular Bragg reflector does not support Bloch mode, therefore in figure 4.10, there is no Bloch mode in a standard Bragg reflector of 4 periods (red line) whereas an extra layer 1.3 times thicker than the Bragg reflector element on top of the mirror yields a pronounced mode at 789 nm (green line). On the other hand, Bloch mode is noticeable for the structure with an irregular layer but on a structure containing 6 periods (black line) of porous silicon films no mode was observed.

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Figure 4.10 The effect of structural arrangement on Bloch surface mode. While regular Bragg reflector without a defect does not support surface mode, scattering and absorption loss of too many layers in the Bragg reflector overwhelm the surface mode even if a defect layer (S) exists.

4.6.4 Effect of the number of periods

Despite strongly localised field intensity, the depth of the Bloch mode in a reflectivity spectrum however, is determined by the number of layers in the bulk Bragg reflector. Increased number of layers maximises reflectivity of reflection band and yielding a higher Q-factor mode as surface mode results from multi-interface interferences, it also increases the loss of scattering of light and intrinsic absorption by silicon. As a consequence, while having smaller FWHM, the Bloch mode becomes shallower with increased layer pairs before dying out in the event of 6 periods shown in figure 4.10. The dependence of the reflectivity minimum in the reflectivity spectra of BSW structures with different Bragg layer pairs is shown in figure 4.11.

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Figure 4.11 Dependence of Bloch surface modes in reflectivity spectra on the number of layer pairs in Bragg reflector. FWHM for structures having 3 (black line), 4 (red line), and 5 periods (green line) are 26 nm, 18 and 15 nm respectively.

The dramatic decrease in field intensity with increased MgF2/TiO2 bilayer periods is reported in ref [29].

4.7 Surface chemistry for robustness, specificity and selectivity

Long term application potential of porous silicon is largely reliant on surface modification. To obtain selectivity in sensing study, in almost all biosensors, transducer surfaces need to be modified with receptors/ligands or other biorecognition elements. Nonspecific adsorption of analyte molecules and other interfering species which is common to all optical biosensors has to be addressed in order to eliminate spurious signals. It is particularly necessary and practicable to modify the large and highly reactive internal surface of porous silicon so that the sensor established on it is stable, robust and resistant to aggressive conditions in biosensing applications.

4.7.1 Surface Passivation

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Surface modification of porous silicon comes into two categories relating to chemical and electrochemical surface reactions. Oxidation-silanization is the mostly widely used method that involves purposefully oxidizing the hydride surface and incorporating functional molecules through Si-O-Si linkage52. A typical representative of this method is reaction between pre-oxidized porous silicon surface with 3- aminopropyltriethoxysilane (APTES) and subsequent activation by glutaraldehyde53, 54. Activated surface is available to immobilize antibodies55, DNA56 and enzymes57. Silanization and amine based linking are usually carried out at room temperature and reaction proceeds quicker therefore it is a straightforward chemistry route. However, it suffers from poor reproducibilities and unpredictable surface modification owing to polymerization of glutaraldehyde53. Another method is based on formation of Si-C bond using functional alkene or alkyne molecules directly on the freshly etched under thermal58, electrochemical59, catalytic60 or radiative61 conditions. Since Si-C bond is more stable than Si-O-Si, this approach can result in more stable surface particularly resistant to physiological environment. Although numerous attempts aiming at electrochemical grafting of organic molecules have shown potential of surface modification under less stringent conditions and even in situ modification during porous silicon formation62, 63, thermal hydrosilylation chemistry is the dominant strategy to convert hydride surface into Si-C based functional organic monolayer64-66. Recently reported ‘click chemistry’ on porous silicon opens up a new avenue to porous silicon surface modification under more mild condition in a more efficient way67, 68.

4.7.2 Hydrosilylation and antifouling layer formation

Surface modification and functionalization used in the study is based on the method established by Böcking et al 69, 70 for porous silicon Rugate filter surface stabilisation, as has been described in previous section (2.2). Undecylenic acid was introduced to replace hydrogen on the freshly etched hydrogenated surface and form a densely packed organic monolayer. After activation by EDC/NHS conjugate reaction, 1-amine hexa- (ethylene glycol) moiety is covalently bonded on top of the organic monolayer for antifouling deterrence. Surface chemistry was monitored by optical measurements. The optical footprint of surface modification on a BSW sample is shown in figure 4.12.

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Figure 4.12 Spectral evolution of a Bloch surface wave structure during a hydrosilylation-

NH2EO6 grafting surface modification process. Hydrosilylation and NH2EO6 attachment reaction induced a red shift in Bloch mode of 19 nm and 17 nm respectively. As chemistry modifications occur in the whole structure, band edge shift caused by Bragg reflection in the bulk structure is noticeable (4 nm and 14 nm, respectively).

4.7.3 Sensing element immobilisation

Interfacing the transducer surface with the right sensing element is the last step to establish a functional and robust biosensor. In this study, gelatin is used as the sensing element to probe the activity of protease enzymes. After the alcohol distal group was activated with DSC/DMAP, gelatin was immobilised. It is worth noting that while previous chemistry modification processes happened throughout the whole porous silicon network, the low bloom gelatin (average molecular weight of 22-25kDa), used in the study, can only be admitted into larger pores (more than 20 nm in diameter) of the high porosity layer but cannot penetrate into the small pores which constitute the low porosity layer. Due to the size exclusion effect of the low porosity layer immediately

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underneath,gelatin immobilization is largely confined in the outmost high porosity layer. Such a distinction in surface modification between the top layer and the holistic structure allows any optical response to the perturbation on the bulk structure to be used as an internal reference to baseline the signal. Figure 4.13 shows optical response of the structure discussed above after gelatin was introduced into the top layer. Gelatin immobilisation caused a red shift in surface mode of 37.5 nm while shift in the band edge is negligible. The figure reveals the ability to differentiate binding activities of interest and non-specific binding by distinctive optical responses attributed to spatially different locations of the structure. Compared with those porous silicon structures such as Bragg mirrors and microcavities which rely on an independent reference control sample to eliminate the impact of non-specific events, it is an advantageous quality of the structural design proposed here.

4.7.4 Sensor responses

The gelatin interfaced Bloch surface wave sensor was exposed to protease in order to test the sensitive and rapid response resulting from structural and morphological design 112

of porous silicon. 5 L aliquots of different solutions of protease was applied to the exposed surface of the structure using a micropipette. The initial reflectivity from the sample was measured and then the solution was applied and left on the sensor surface for a fixed time of 20 minutes, before being removed using the pipette. During the exposure the porous silicon structure was maintained in humid conditions to avoid drying. The reflectivity was then measured again and the sample was spotted with Milli- Q water to remove any buffer salt residue deposited on the surface. For control tests 5 L of phosphate buffer saline (PBS) solution was used, containing NaCl 137 mmol/L, KCl 2.7mmol/L, Na2HPO4 10 mmol/l, KH2PO4 1.76 mmol/L. Due to the catalysis of protease, gelatin immobilised in the top layer was cleaved at some specific sites, leading to collapse of the gel network and reduced local refractive index. Such a negative RI change is detected by the Bloch wave and an appreciable blue shift in the reflectivity spectrum is expected. Figure 4.14 shows the distinct responses of the sensor. In a control test with PBS, both surface mode and the band edge kept unchanged after the test, indicative of the robustness of the sensor as a result of surface chemistry modification. After both tests, band edge remained at the original position suggesting the bulk structure was not perturbed by the cleavage reaction and its products. This effect can be exploited as a useful reference to control the protease detection test by excluding the undesirable shift caused by non-specific activities in the bulk Bragg mirror structure.

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Figure 4.14 Responses of the BSW sensor to subtilisin and PBS, respectively. While protease exposure caused a blue shift of 8.5 nm, PBS treatment did not shift the surface mode, suggesting the cleavage of gelatin by protease. In both control and enzyme tests the band edge remains unchanged, indicating intact bulk mirror structure. The band edge can be used to monitor the non-specific events occurring in the bulk Bragg structure and therefore can potentially be a self- reference.

4.8 Conclusion

Easily achievable structures and controllable fabrication techniques to acquire ample morphological, structural and chemical benefits make porous silicon an attractive option in constructing high quality optical and optoelectronic devices. The capability to form optical films and multi-thin films with tunable film thickness and their effective refractive index associates porous silicon with photonic crystals. The large internal surface of porous silicon has long been a dream for sensitive sensor. The possibility to flexibly arranging component layer sequences provides a very effective way to accomplish spatial enhancement of field for maximise light matter interaction in biosensing application and more importantly select the location of enhancement for easy manipulation of both sensing element and target analyte. With the benefits brought with porous silicon multilayer one dimensional photonic crystals, a new type of sensor platform has been proposed, designed and fabricated. It is shown that porous silicon can be etched into a structure that sustains Bloch surface wave and localise light in the vicinity to the interface with other medium if the geometrical parameters of a regularly periodic multilayer are chosen properly. Unique porous matrix is a suitable host for binding activities. Non-surface mode localisation in dielectric medium ensures the sensing events are fully covered by the evanescent Bloch wave rather than being swept by an exponentially decaying tail in the case of SPR. Bloch mode position is determined by the layer where the mode is sustained. Distinguished optical features closely related to particular parts of the structure make Bloch surface wave structures, as described above, an advantageous sensing vehicle over other evanescent techniques. The number of component layers has huge impact on the Bloch mode. Higher number of layers leads to sharper mode but tends to overwhelm the mode with losses.Overall, 4 periods of porous silicon films is sufficient for surface wave realisation.

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While an unstable surface holds back many attempts made on porous silicon, high reactivity opens up a way to break the dilemma. Surface chemistry is vital in expanding applications of unstable and reactive porous silicon. On the success of previous work on mesoporous silicon Rugate filter, surface modification has been undertaken on Bloch surface wave structure based on mesoporous silicon. Optical responses during surface modification manifest the effectiveness of surface passivation and antifouling layer formation with a red shift in Bloch mode of 19 nm and 17 nm respectively, which is consistent with well documented results from Rugate filters22. Design in layer sequence allows one to exclusively interface the top layer of the structure with proper sensing element. By exploiting pore size contrast between the top layer and the neighbour low porosity layer, gelatin is immobilised in the top layer. Optical measurement shows dramatic shift (37.5 nm) in Bloch mode whereas shift in band edge is negligible (1 nm). Such a specific response can potentially be capitalised on as an internal reference to obviate interference from specific adsorption (desorption) in nonspecific area.

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Chapter 5 Porous silicon Bloch surface wave sensors for protease detection There exists a need for quick and sensitive techniques to detect protease enzymes and their activity level because of their widespread existence and important role in many life processes1. Easy fabrication, unique morphology, compatibility with IC chip processing technologies and reliable surface chemistry make porous silicon an almost ideal candidate for biosensing. In the previous chapter, the author proposed a new porous silicon photonic crystal based structure and showed the existence of Bloch mode sustained by such structures. This pronounced mode, which is sensitively influenced by the thickness and effective refractive index of the top layer, can be utilized as a sensing signal. Introduction of small molecules into certain parts of the porous matrix induces significant and specific shifts in the Bloch mode. Herein, based on the biosensor discussed in the previous chapter, getatin-subtilisin was used as a model system to seek the possibility of protease assay as well as obtain an insight into proteolysis kinetics in a specific fashion on porous silicon Bloch surface wave biosensor. Exposure to protease initiates catalytic degradation of gelatin gel network which is exclusively formed in the top layer of the sensor, causing a blue shift in Bloch mode. Principally, as the bulk structure is hardly perturbed by the catalytic degradation, products of digestion are expelled by the antifouling species established in the surface modification steps, the band edges do not exhibit shifts as significant as that in surface mode. The insensitivity of the band edge can be utilised as an internal reference to exclude nonspecific adsorption and bonding. 5.1 Protease in living systems Proteases, also known as proteolytic enzymes, are globular, water soluble proteins that function as enzymes to specifically cleave or degrade proteins by catalysing the hydrolysis of amide bonds in peptide chains, either from the N or C termini (aminopeptidases and carboxypeptidases, respectively) and/or in the middle of the 120 molecule (endopeptidases) 2. Specific cleavage of peptide bond in protein plays an important role in activation and control of cellular metabolic processes: -removal of old and unused proteins. This is an essential part of the turnover pathway of all proteins in the cells and affects cell growth. - degradation of proteins and peptides for nutritional purposes - defense mechanisms against intrusive proteins and peptides - remodelling the extracellular matrix to facilitate cell migration, both a natural bodily function and important in cancer metastases - control of protein activity Their primary role was long considered to be protein demolition relevant to food digestion and intracellular protein turnover. However, it was discovered recently that precise cleavage of proteins by proteases turns out to be a very subtle means of regulation3. By degrading proteins and generating new protein products, proteases are critical in the controlling a large range of key physiological processes4, 5, such as DNA replication6, cell-cycle progression, cell proliferation and death7, tissue remodelling, haemostasis (coagulation), wound healing and the immune response8 and therefore play an important role in pathologies including cancer9-11 and cardiovascular disease12. In cancer, high levels of protease activity are associated with invasive and metastatic cancers. In cardiovascular disease, proteases are active in apoptosis, tissue remodelling, and modification of cardiac proteins. The activity of enzymes can be indicative of normal or abnormal cellular function and is often used to detect infections13. Some toxins participate in physiological processes through protein cleavage14. Therefore, proteases have been seen as ideal biomarkers for the diagnosis of disease15 and important pharmaceutical targets16, 17. Investigation of the pathological and physiological functions of proteases requires sensitive assays to detect their activity in complex tissue samples and other biological matrices. Thus, detection of proteolytic molecules and their level of activity are of particular significance in clinical diagnosis and enzyme engineering. In the face of increasing bioterrorist threats, there are also increased interests in proteases detection in homeland security. 121

5.2 Protease detection techniques Enzymes are analysed based on activity assay due to the specificity of action on a certain substrate. Detecting enzymes by the means of their catalytic action on substrates is an advantageous property over other biological reactions in terms of sensitivity thanks to the in-built signal amplification that arises because a single protease molecule has the capacity to break many peptide bonds and produce vast amount of products including smaller-size proteins and peptides. An enzyme assay usually involves determining the rate of product formation or substrate depletion during the enzyme catalysed reaction. Some methods currently used to assay proteases are highlighted in a number of reviews18-20.

5.2.1 Zymography

Zymography is a popular proteinase assay technique since 1960s. The enzymes are analysed through electrophoresis of polyacrylamide gels containing copolymerized protease substrate, mainly gelatin. Electrophoresis is generally performed in sodium dodecylsulfate (SDS) and proteases are then renatured, enabling the hydrolysis of the substrate. After staining, the zones of digestion may be evidenced and/or quantified. Zymography has been used to visualise21 and quantify22 proteinase activities. Using complex of purified metalloproteinase-2 (MMP-2) and its tissue inhibitor, detection limit of 2 pg enzyme was demonstrated in Kleiner and co-worker’s work18. In an improved single-step staining method23, a detection limit of 32 pg for pro-MMP-9 and a linear range below 1 ng was achieved. Zymography has also been used in in situ monitoring24.

5.2.2 Spectroscopic techniques for enzyme assays

In enzyme assays, spectroscopy and spectrophotometry are major techniques used to determine the enzyme activity by targeting the change in optical properties of substrate or the products. These changes are embodied by appearance, change or disappearance of emission (fluorescence), absorption or transmission of the probing light.

5.2.2.1 Fluorescence spectroscopy and colorimetry 122

Fluorescence spectroscopic methods are based on the light intensity after interacting with the analytes. As a result of enzymatic reaction, due to the energy exchange between the probing light and the analytes, depending on the optical properties of the luminescent tag attached to the substrate, fluorescence can be generated, enhanced or quenched. The intensity of excited fluorescence, extent of enhancement, or quenching is related to the amount of enzyme and its activity which triggers the fluorescence change. Although fluorescent proteins are available as the substrates for proteolysis, more prevailing substrates are those modified with fluorophores or chromophores such as dyes. Several assays detect unmodified substrate reactions while in most cases, detection of enzymes is based on detection of protein derivatives liberated as hydrolysis products of an enzymatic reaction such as amino acids. Commonly, protease assays use fluorogenic25, 26 or chromogenic27, 28 peptide substrates. In one case, fluorogenic protease substrates are constructed from a fluorescent probe and a quencher that are located on opposite sides of the cutting site18. When the protease cuts the substrate, the probe is liberated, which generates a highly fluorescent product. Despite high sensitivity, molecules are traditionally detected with fluorescence approaches that involve tedious labelling processes. Labelling can exert impact on activity of enzyme the immobilised substrate.

5.2.2.2 Förster resonance energy transfer (FRET)

Fluorescence resonance energy transfer, also referred to as Förster energy transfer, is a novel approach taking advantage of the energy exchange between different materials in sub-nanometer or molecular scale proximity (~100Å)29. FRET occurs when two proximal fluorophores, with one acting as a donor (of photon) and the other as the acceptor. The emission from the donor excited by an external source is absorbed by the acceptor which gives off characteristic emission. The extent of acceptor emission enhancement or the donor emission quenching is taken as energy transfer efficiency of the FRET. FRET energy transfer efficiency and its change indicate the molecular interactions undergoing in the host materials. Since the separation distance of fluorophores is on the molecular scale, FRET has been developed into one of the most 123 popular intramolecular biosensors to detect small molecules30-32 in cell biology study. Enzyme induced proteolytic cleavage is a particular application which FRET can find because of the significant molecular rearrangement during the proteolysis that allows large changes in FRET signal. There have been a significant number of reports on protease activity detection based on FRET using fluorescent proteins33-35. More recently, quantum dot based FRET system has been developed to overcome some of the drawbacks associated with fluorescent proteins such as pH sensitivity, susceptibility to photo/chemical degradation, relatively narrow absorption coupled to broad emission spectra. With wide absorption band, high extinction coefficients, tunable emission wavelengths and unique photophysical properties, quantum dots are excellent photon donor in FRET, exhibiting higher FRET efficiency36. A schematic diagram of quantum dot based FRET is shown in Figure 5.137.

Figure 5.1 Schematic diagram of the QD-dye-peptide FRET-based sensor configuration.

Dye-labeled peptides containing appropriate cleavage sites for protease are self-assembled onto the QD surface. FRET from the QD to the dye quenches the QD PL. FRET efficiency changes induced by proteolytic cleavage of the peptide reveal the amount of protease (activity). Figure adopted from ref [37].

A specific peptide substrate flanked with a dye is conjugated to a quantum dot. The emission of quantum dots is quenched as a result of FRET. When the conjugate is exposed to protease, the peptide is broken up at the cleavage site. Cleavage of the 124 peptide as a linker allows the disintegration of the acceptor dye from the quantum dot and disables FRET. As a consequence, the fluorescence of quantum dots is enhanced. Sapsford et al37 showed a lowest detection limit of 6.2 nM of trypsin using Cd-Se core-shell quantum dots centred at 530 nm and Cy3-maleimide mono-reactive dye. Medintz et al used quantum dot based FRET sensor to monitor the enzymatic kinetics of caspase, thrombin, metalloproteinase and chymotrypsin for different synthetic substrates. Yao and co-workers38 demonstrated that by conjugating a short peptide with bioluminescent molecule luciferase as a donor and quantum dots (655 nm) as an acceptor, gelatinase (MMP-2) is detectable at concentration of 30 pM, at the expense of 24 hour incubation.

5.2.3 Spectrophotometric methods

Most enzyme assays are based on continuous or intermittent measurement of the concentration of substrate or the product released in the reaction in order to obtain the rate of substrate consumption or product formation. Proteolysis accumulation or substrate depletion can be monitored by exploiting the intrinsic absorption of these substances which is usually characterized on a spectrophotometer. One of the most convenient methods, referred to as A280, which is based on the measurement of UV absorbance at 280 nm, has been widely used to monitor protein evolution during proteolysis39. UV absorption of proteins is due to the presence of aromatic amino acids, mainly tyrosine and tryptophan. Many protocols measure the degradation of substrates due to the catalysis of the proteolytic enzymes through the determination of the concentration of trichloroacetic soluble acid amino acids and peptides40. Some of the protein fragments and amino acids generated in the proteolysis can be sensitized by suitable chemicals such as ninhydrin41, 42 and trinitrobenzene sulfonic acid43 and detected on UV/ Vis spectrometer. However, there are other types of assays which specifically and directly measure the absorbance of the hydrolysis reaction samples by using artificial substrates such as azocasein44and azogelatin45 which, when hydrolyzed, releases coloured products while the substrate can be precipitated by trichloroacetic acid. As an extension of colorimetric and fluorimetric methods, various plate readers, similar 125 to those used in ELISA, have been designed to improve the assay throughput. Although based on Lambert-Beer law, the absorbance is more related to the volume of the sample. Inaccuracy can occur as in contrast to the cuvette whose optical path is well defined, the microplate well radius varies among models, in particular when small volumes are used. The presence of meniscus may also distort the linear relationship.

5.2.4 Radioactively labelled substrate for enzyme assays

The hydrolysis product can also be detected by the use of a peptide that has been radioactively labelled 46. Appearance of radioactivity in the supernatant is evidence for the presence of a peptide. Similarly, a peptide can be engineered that is overall neutral in charge but contains a highly charged, radioactively labelled fragment that is liberated upon cleavage47. The cleaved fragment is captured on an ion exchange resin and detected through its radioactivity. However, these methods are all sensitive to nonspecific proteases and thus vulnerable to interferences. 5.3 Label-free biosensors for enzyme detection Despite the fact that the abovementioned techniques involving labeled substrates enjoy higher sensitivity and selectivity, detection requires complicated and cumbersome labelling and incubation processes. Labeling tags can be expensive or are not easily available. Worse still, these methods including FRET commonly suffer from interference from labels because labeling may sterically hinder some of the active binding sites and limit the reactivity of the substrate. Use of excessive amounts of reagents may have potential health risk implications. By contrast, label-free biosensors based on various reaction mechanisms and transduction concepts have been developed as an alternative to address problems such as low throughput and the cost involved in all techniques mentioned above. Some label-free biosensors exhibit sensitivity comparable with traditional assay methods requiring labeling. Using gelatin coated electrode, Saun et al48 reported a impedance spectroscopy technique for collagenase detection in the air with a lowest detection limit of 0.01 mg/ml collagenase. Zhao et al49 showed a sensitive magnetic sensor for protease assay. In this technique, the spin-lattice relax time of water

126 was changed by the interaction of biotinylated substrate fragments generated in the enzymatic reaction and magnetic nanoparticles flanked avidin. The changes were measured using magnetic resonance and related to the MMP-2 concentration as low as 19 ng/ml. A microcantilever sensor was reported by Raorane et al50, who studied the degradation of cysteamine catalyzed by trypsin which caused changes in surface stress. Among all transduction techniques, optical sensors are the most popular sensing methods. Wankam et al51 reported the study of enzyme reaction by surface plasmon resonance (SPR). There was linear dependence between the SPR shift rate induced by thickness reduction of immobilized bovine serum albumin and the concentration of subtilisin in a range of 2.5 μg /ml –1.25 mg /ml. This dependence can be utilized for enzyme quantification. The work of Pieper-Fürst et al52 on SPR showed a signal amplification factor of 114 and a detection limit of 1 pM MMP-2 with the help of colloidal gold nanoparticles. Whispering gallery modes sustained by microsphere resonators were utilized by Hanumegowda and colleagues53 to detect the activity of trypsin where shifts in the whispering gallery mode are indicative of changes in thickness of BSA deposited on the microsphere as a result of trypsin catalysis were monitored. The mode shifts were associated with the activity of trypsin. Thanks to the high Q factor of the microsphere (2×105), a sensitivity was estimated at 10-8 mg/ml (420 pM) or 10-4 Units /ml in a wide range of 10-7-10-2 mg/ml. Applications of these methods, either suffering from low sensitivity, demanding sophisticated instrumentation or difficult device fabrication and optical alignment, are restricted. 5.4 Protease assays using porous silicon biosensors

5.4.1 Immobilized enzyme for substrate detection: activity assay

As has been discussed in chapter 1, by any measures, porous silicon is almost an ideal candidate for biosensor and can be tailored to support diverse transduction mechanisms. With outstanding optical properties such as photoluminescence, its easily controllable nanoscale architectures and flexible surface modification chemistry, porous silicon has long been one of preferred materials to be considered for biosensor implementation.

127

Porous silicon has a unique advantage in the detection of proteases and monitoring of enzymatic reactions; its large internal surface area and tunable porosity/pore sizes can accommodate either enzyme of different sizes, or substrates ranging from small peptide chains to large protein molecules. Substrate immobilisation methods include physical adsorption, covalent binding, entrapment, encapsulation and cross-linking. Thanks to its favourable morphology, simple porous silicon structures can be used to monitor the enzyme activity in a real time manner, as demonstrated by Orosco et al54. The sensor capitalized on the abruptly varied pore sizes of two neighbouring layers in pepsin loaded double layer structure to allow the selective infiltration of digestion product into low porosity layer. Specific optical response as a result of selective infiltration indicates the proteolysis progress.

5.4.2 Protease detection using immobilized substrate

The ability to produce porous silicon as a multilayered film enables the engineering of one-dimensional photonic crystals. The ease of fabrication of complex optical structures with porous element and excellent optical properties has provided impetus to establish label-free biosensors using the hierarchical porous silicon structure for biosensors. As an example, the Sailor Group55 reported a zein-coated multilayer mesoporous silicon Rugate filter to monitor enzyme activity. The porous silicon structure was methylated and spin-coated with a hydrophobic protein which formed a thin film. Exposure of methylated porous silicon to pepsin led to breakup of zein thin film and changed the colour of the film. Small fragments resulting from the protein cleavage infiltrated into the pores of porous silicon and caused a red shift in the reflectivity spectrum. Based on the red-shift in peak resonance of the Rugate filter structure, induced by enzyme mediated digestion and production infiltration, 7.2 pM of pepsin could be detected by visual inspection. Using similar structure spin-coated with gelatin, Gao et al56 demonstrated the detection of gelatinase- 2 (MMP-2) through the optical response to as little as 1 μl gelatinase application at room temperature. Colorimetric observation combined with spectral measurement revealed a lowest detectable gelatinase concentration of 0.1 pM, two orders of magnitude lower than that obtained in 128 zymography. Gelatin spin-coating conditions for different permeability were investigated. In contrast to zein coated method, gelatin is water permeable and more amenable to aqueous detection. However, the methods in these reports are semi-quantitative and required time consuming incubation. Gooding and co-workers57 showed that by covalently immobilizing gelatin in high quality Rugate filters, a substrate based protease biosensor displayed high sensitivity with a defined optical response linearly dependent on the concentration of protease. This method enabled detection of MMP-2 concentration as low as 37 nM in 240 min. Furthermore, in situ monitoring of proteolysis of gelatin catalysed by MMP-9 secreted from live cells (macrophage) was also demonstrated58 on the same structure and detection limit was pushed down to 0.37 pM (1 pg/ 100 μl). By estimating the number of protease molecules in individual pores under a probing light beam of 2 mm, Kilian identified the dynamic range of protease detection and deduced that 0.0006 protease molecules/ pore can be detected by this technique. The surface chemistry that assured sensor robustness and the sensing rationale of the Rugate filter sensors in ref58, as is shown in Figure 5.2, will be succeeded and adopted in this thesis.

Figure 5.2 (a) Schematic representation of chemical moieties grafted within mesoporous PSi: (1) hydrosilylation of undecylenic acid onto the Si-H surface (black), (2) activation and coupling of hexa(ethylene glycol) amine (red), (3) activation with DSC, and (4) immobilization of gelatin

(green). (b) Schematic depiction of gelatin-loaded pores before (upper) and after proteolysis 129

(bottom). The whole structure is impregnated with cleavage fragments that need to be discharged in order to achieve reduced effective refractive index. Figures are reprinted from ref

58.

Porous silicon multilayer can be readily harnessed to create resonators, such as microcavities. Resonant structures have the advantage of multiple light-matter interaction conducive to sensitivity enhancement thanks to narrow resonant peak allowing for reliable 0.1-1 nm resolution. Porous silicon microcavity structures have also been reported for enzyme activity monitoring59-61. 5.5 Protease detection on porous silicon Bloch surface wave biosensors As was discussed in the previous chapter (4.5.1), there exist some intrinsic hurdles to mesoporous silicon microcavities and Rugate filters for biosensing applications. In mesoporous regime, the pore sizes are 10-50 nm, large molecules such as majority of proteins and enzymes cannot penetrate through. High porosity contrast in monolithic microcavities exerts nearly an insurmountable blockade for those biomolecules to access the sensitive central area of the microcavities. In order to facilitate the infiltration of the analytes, some post fabrication treatment was needed to increase the pore entrance for easier ingress of larger molecules, which inevitably undermines the optical properties of the microcavities (broadened resonance peak)62, 63. Although Rugate filters have larger pores (50-60 nm), the thick structure (a few μm) required for narrow reflection peak retards diffusion of analytes and in the event of enzyme assays, the product discharge. In the previous chapter, the author proposed that Bloch surface wave structure can be a solution to the above problem by providing an open sensing space and simple structural constitution.

5.5.1 Sensor fabrication

Bloch surface wave structure discussed in this thesis was fabricated on p+ highly doped (resistivity 0.0015-0.0020 Ωcm,) silicon wafers as described in chapter 2 (2.2.1.2). The

130 sensor based on a Bragg reflector contains a 4 layer pairs of low and high porosity layer as the structure backbone. An extra high porosity layer at the end of the sequence and immediately next to a low porosity layer acts as a sensing layer.

5.5.2 Surface modification and substrate immobilisation

Freshly fabricated porous silicon surface is covered with hydride. Terminal silicon-hydrogen (Si-Hx, x=1, 2, 3) bonds are not stable and tend to oxidize slowly when exposed to ambient air thus is susceptible to the attack of trace amount oxygen and water. To establish a robust and reliable biosensor, it is crucially important to protect the sensor from its environment which is primarily aqueous and aggressive. Though oxidation is an easy approach taken by a number of researchers to stabilise and functionalise porous silicon surface, its drawbacks such as vulnerability to further nucleophilic attack and negative impact on the optical properties excluded it from being the preference for passivation technique. In contrast, replacement of Si-Hx moieties with Si-C covalent bond proves to be a promising strategy in view of the high stability of Si-C bond and possibility of further funcionalisation with well established conjugate chemistry. In this thesis, surface passivation and subsequent derivatization of porous silicon were conducted in accordance with the methods in the pioneering work of Kilian et al57. The details of hydrosilylation and further functionalisation chemistry were described in chapter 2 (2.2). Enzyme based biosensors usually involve immobilisation of either enzyme or the substrate on a solid surface. The extensive internal surface of porous silicon allows for immobilisation of large amount of molecules compared with planar materials. Numerous studies investigating immobilisation method, support materials and immobilisation conditions showed that while porous silicon is a suitable biocatalytic microreactor64, 65, it has some drawbacks such as enzyme activity loss due to conformational change (allostery)60 and short lifetime of the sensor due to poor stability of enzymes. Alternatively, a variety of substrates can be immobilised to form protease biosensors for both activity assay and concentration quantification purposes. These substrates include a range of more specific synthetic peptides and full proteins with 131 broad specificity as universal protease substrates such as casein, haemoglobin, gelatin and albumin. By incorporating ranges of peptides or proteins containing certain amino acid residues, sensors can afford dramatically improved stability and specificity for many utilities such as clinical detection.

Figure 5.3 Schematic structure of a short fragment of gelatin.

Gelatin is a denatured product derived from partly hydrolysis of naturally occurring parent protein, collagen which is the main constituent of extracellular matrix (ECM). Gelatin is chosen as a universal substrate of proteases in preference to other proteins such as casein because it is susceptible to proteolysis by a broad variety of proteases, especially microbial proteases66. Covalent immobilisation of gelatin, as was suggested, exploits the free amino acid in arginine residue67 through succinimide ester assisted conjugation. In this study, gelatin was attached after the hydroxyl group in the EG6 antifouling layer was activated with disuccinimidyl carbonate (DSC). In the previous work by Kilian, the qualitative material change in the bulk porous matrix was monitored using Fourier Transform Infrared (FTIR) spectroscopy during surface modification and functionalisation. Quantitative identification of element appearance and loss in mesoporous silicon was achieved by X-ray Photoelectron Spectroscopy (XPS). For details of surface characterisation the readers are referred to

132 the reference68. In the present study, reflectivity spectra were recorded following each step as an indicator of progress in surface modification. Change in reflectivity spectra in the surface modification processes is shown in Figure 5.4.

Figure 5.4 Optical shift accompanying the step-wise surface modification processes. With the progress of surface chemistry, both the Bloch mode and band edge move to the longer wavelength. Note that gelatin immobilization only cause shift in the Bloch mode, indicating the exclusive bonding of gelatin in the very top layer.

5.5.3 Protease detection using gelatin modified Bloch surface wave biosensors

The sensor interfaced with specific recognition species is ready to be tested for the ability to probe protease enzymes. This was done by spotting protease solution on the sensor top using a micropipette and left in contact with the solution for a fixed period of 133 time, as is illustrated in Figure 5.5a. Figure 5.5b shows that under the coverage of the enzyme solution, gelatin helices are broken down into shorter peptide debris and amino acids. Instead of going into the small pores beneath, these small fragments diffuse out of the pores.

Figure 5.5 (a) Diagram of the porous silicon film mounted on the surface of the prism using a cover glass as a substrate and refractive index matching liquid. During the sensing experiments the biological suspension is applied to the top surface and permeates through the porous film.

After a fixed period of time the solution is removed from the film and allowed to dry. (b)

Illustration of gelatin cleavage on the sensor in discussion. As gelatin is majorly anchored in the top layer, proteolytic cleavage takes place in this layer accordingly. Cleavage products diffuse away quickly instead of going into small pores underneath.

Subtilisins are a homologous family of serine proteases. They have a common three-dimensional structure and similar catalytic and binding sites, but they differ significantly from each other in catalytic efficiency (defined by kcat / Km, see below) as a

134 result of a variation in the mode of substrate binding69. The substrate reactivity is determined by sub-site interactions between the extended substrate binding site and the polypeptide substrate. Subtilisin Carlsberg (M=27,300, Stokes-Einstein radius approximately 2.1 nm70), sometimes called subtilisin A or Alcalase, was employed in this study as the model protease. After the sensor is hydrated with 5 μl phosphate buffered saline (PBS), 5 μl subtilisin solution in PBS (×1, pH=7.4) is applied onto the sensor and covered with an Eppendorf tube to prevent liquid evaporation and keep the reaction in solution. At the end of the scheduled reaction time, enzyme solution was removed and the sensor chip was rinsed with 5 μl Milli-Q water to eliminate any buffer salt precipitation and reaction residue that may cause false negative. A water rinsing step was necessary because salt residue from buffer deposited on the internal surface increased the effective refractive index of the porous silicon matrix, offsetting the shifts in proteolysis tests and caused red shift in control tests. The role of the water rinse can be seen in the comparison depicted in Figure 5.6. As can be seen in Figure 5.6 (a), after proteolysis was terminated by removing 0.01 mg/ml subtilisin after 10 min exposure, the Bloch mode shifted 8 nm from the hydrated position. A large shift of 31 nm was observed only after rinse with 5 μl of water (b), suggesting the desirability of flow cell utility for optimised sensing operation. Noticeably, after cleavage, there was a significant net red shift with regard to the original position of the band edge after proteolysis, possibly associated with non-specific adsorption of buffer salts residue and by-products of the enzymatic reaction deposited throughout the entire photonic structure. Build-up of salts and cleavage debris can be simply eliminated by rinsing with water. After the water rinse, the band edge returned to its original position and the Bloch mode experienced a massive blue shift of 31 nm, suggesting the porous silicon bulk structure was not influenced by the proteolysis events as a result of quick diffusion and nonspecific adsorption deterrence by the antifouling monolayer. The data showed here and after enzyme application and then after the water rinse. Overall, only shifts in the Bloch mode are specific to the enzyme action.

135

Enzyme assays are usually conducted at the early stage of the enzymatic reaction when the substrate is not significantly consumed (<5-10 %) and the reaction rate (initial rate) is solely proportionally related to the concentration of the enzyme as a catalyst. For a kinetically controlled enzyme reaction, the initial rate is proportional to the enzyme concentration (zero order for substrate). A linear dependence of initial rate on the input enzyme concentration is the basis of enzyme detection in this study. Quantification of enzyme can be achieved by ascertaining either the length of time required for the maximal substrate digestion or the greatest dilution of enzyme which gives observable 136 substrate conversion in a fixed time period. During the reaction, optical signal corresponding to the concentration of substrate or product is checked at a fixed time in the reaction to form a progress curve. To estimate the initial rate, a concentration of product or remnant substrate at time point close to the origin is taken. This is an arbitrary and subjective way of initial rate estimation. Initial rates can also obtained by linear fitting at the early stage of the progress curves. By running a series of reactions at different enzyme concentrations, a series of initial rates can be related to enzyme concentrations. Alternatively, initial rate can be obtained by linear fitting the time course (progress curve) at the early stage (close to time zero). With lowered enzyme concentration, initial stage becomes longer. In this study, fixed time measurement of reflectivity was carried out to obtain the optical shift data for subtilisin quantification. For high protease concentration reaction, reaction was terminated after 10 min and reflectivity spectrum was recorded. At lower enzyme concentration, optical shift in a time range of 20 min~300 min was taken to estimate the initial rate. Control tests were performed using PBS. Figure 5.7a shows an appreciable blue shift of 2.5 in the Bloch mode after cleavage catalysed by 0.0001mg/ml subtilisin (3.7 nM) for 90 min whereas in control test (Figure 5.7b) with PBS, 0.5 nm blue shift was observed, indicating the stability of the sensor surface. At the lowest subtilisin concentration (0.0001 mg/ml), the Bloch mode blue shifted by 0.7 nm (after background subtraction). As the red shift induced by gelatin loading into the sensor is 40.5 nm, this is equivalent to 1.7 % of gelatin cleavage. At the highest subtilisin concentration (0.01mg/ml), on the other hand, the Bloch mode blue shifted 13.9 nm in 10 min, which is larger than that reported for Rugate filter in the work of Kilian et al58, indicative of 34 % cleavage of immobilised gelatin.

137

Figure 5.7 Optical shift of the Bloch mode after the sensor chips were exposed to 0.0001 mg/ml

(3.7 nM) subtilisin (a) and PBS Silane buffer solution for 90 min. Unchanged mode widths on both occasions indicate the robustness of the sensor and homogeneous cleavage. The initial rates of the proteolysis, represented by the overall shift rates of Bloch mode, taken by recording the mode shift over the arbitrarily scheduled reaction time in each reaction, are listed in Table 5.1.

Table 5.1 Initial rates, represented by shift rates of surface mode under the catalysis of subtilisin, corresponding to subtilisin input concentration. Subtilisin Concentration, M Average Velocity, nm/min 3.67E-10 0.0044 3.67E-09 0.0035 3.67134E-08 0.35 1.1014E-07 0.50 1.83567E-07 0.78 3.67134E-07 1.39

In Figure 5.8,the initial rated were plotted against the concentrations of subtilisin. A

138 linear relationship between the mode shift rate and subtilisin concentration is apparent. The practice of extracting initial rate using different end point time is justified by the fact that at low enzyme concentrations, degradation of proteins is very slow (up to 10 days to be degraded)71. Taking the resolution of the spectrometer used in data acquisition and the stability of the enzyme into consideration, initial stage on a time scale of 300 min for digestion under the mediation of 0.37 nM subtilisin, is reasonable.

Figure 5.8 Dependence of average velocity of the Bloch mode shift on the concentration of protease. Linear relationship indicates that at all concentrations studied, gelatin cleavage is controlled by protease catalysis. The linearity is the basis of protease quantification. Error bars are standard deviation based on replicate runs of at least 4.

As can be seen in figure 5.8, in a broad range (from nano molar to sub-micro molar), the

139 initial rate of gelatin degradation linearly increases with subtilisin concentration. The linear relationship between initial rate and enzyme concentration indicates the dominance of enzyme catalysed degradation and exemption of the reaction from mass transport (diffusion) restriction. This proportional relationship can be utilized in protease detection. All rate data were recorded at room temperature which varied from season to season and results in lower rate than that obtained at standard incubation temperature reported in most literatures (37˚C). The lowest detectable subtilisin concentration this study is 370 pM, which is comparable with the published results on whispering gallery mode resonators53. Given sufficient stability of enzyme and sensor surface, this concentration can be pushed down under prolonged incubation time. However, in consideration of the simplicity of sensor construction, shorter incubation time and the advantageous open sensing space it offers, this sensor design will bring out more benefits and has the potential to serve wider application purposes, such as reaction kinetics monitoring.

5.5.4 Enzymatic kinetics observation on Bloch surface wave biosensors

In addition to identification and quantification, kinetic studies are another important aspect of enzyme characterisation and are of crucial importance to several research fields, including biochemistry, biotechnology, pharmacy and medicine. Kinetic study on the nano-scaled biosensor surfaces is more likely to reveal the real picture of enzymatic catalysis occurring in physiological scenarios.

5.5.4.1 Simplified enzymatic kinetics: Michaelis-Menten equation

A single substrate enzymatic reaction can be simply described by the following scheme though more complicated reaction mechanisms are involved:

In a period at the early stage, breakdown of the enzyme-substrate complex ES is fully

140 counteracted by its formation through binding equilibrium. As a result, after an abrupt increase (burst), the ES complex concentration maintains nearly a constant value. This period is referred to as (quasi)steady-state, as is depicted in Figure 5.9a. Enzymatic reaction can be described by Michaelis-Menten (MM) equation (5.2) which stipulates the relationship between the initial rate and the total enzyme concentration, depending on input substrate concentrations. This dynamic relationship between initial rates and the starting substrate concentrations can be illustrated by Figure 5.9b. If the substrate is maintained excessive, enzyme can be quantified by running a number of reactions with different enzyme concentrations whereas following a single reaction can reveal kinetic information of enzyme.

Figure 5.9 a) Depiction of different stages enzymatic reaction; the steady state region (labeled) occurs where no significant substrate consumption or production accumulation and ES complex remains constant concentration. b) Initial rates exhibit varied dependence on input substrate concentrations. c) Time courses (reaction progress curves) of reactions at different levels of

141 enzyme. r1-r4 are initial velocities of reactions, obtained by linear fitting of the initial stages of the reactions, corresponding to variable enzyme concentrations ([E]1-[E]4.). Initial velocities and kinetic characterization can all be obtained from progress curve fitting.

The MM equation is established on the basis of a number of initial rate measurements with different substrate concentrations.

௏೘ೌೣሾௌሿబ ௞೎ೌ೟ሾாሿబሾௌሿబ (ݒ଴ ൌ ൌ (5.2 ௄೘ାሾௌሿబ ௄೘ାሾௌሿబ where v0 is the initial velocity, often expressed as the rate of substrate depletion or product accumulation. ሾሿͲand ሾሿͲ are initial concentration of substrate and enzyme, respectively. Vmax is the maximum possible initial velocity an enzyme can achieve. It is approached only at high substrate concentration when enzyme is completely saturated with substrate. Essentially, MM equation governs the relationship of catalysis efficiency and reactant level by considering both the dynamic binding equilibrium () and enzyme turnover ( ). In essence, Km is the initial substrate concentration under which half the Vmax is approached, while kcat is the rate constant of enzyme-substrate complex breaks up and products result. The MM equation depicts the kinetics using the constant obtained under steady-state which is observed when the substrate concentration is in excess of enzyme so that enzyme can be saturated by the substrate. As a matter of fact, the coefficient between the reaction rate and enzyme concentration reveals the kinetic information of the enzyme catalyzed reaction. It is suggested that though obtained at initial stage, the MM equation can be used to analyse the time course of the enzymatic reaction as steady-state can last until the exhaustion of the substrate72. The fact that the steady-state holds for much longer than initial phase allows us to use time-resolved sensor-gram to estimate kinetic constants. Analyses of progress curves over time can be useful, because the time-courses contain abundant information relating to both the binding and catalysis properties of the enzyme. Kinetics data can be obtained by monitoring a single reaction. Therefore, with only a fraction of the number of experiments, analyses of time-course of reactions provide the same information as that obtained by classical initial-rate approaches which require legions of parallel 142 experiments.

5.5.4.2 Kinetic monitoring on BSW biosensor surface

Despite the deep understanding of enzyme kinetics in solution, bulk aqueous rates of proteolysis fail to indicate protease performance in physiological context, as in-solution digestion is an inherent slowed process where low concentration of proteins to be digested varies due to mass transport restrictions. A vast majority of biological activities involve surface based modification, degradation and biosynthesis. In vivo, proteins (ECMs) are often organized in a gel state which is swollen by a large amount of solvents around. Cell invasions are possible only when these dense networks are disrupted by proteolysis. For this reason, studying surface enzymatic kinetics is the key to understanding of interfacial enzyme cleavage and is under extensive investigation. Among these matrices that support the enzymatic cleavage reaction, nanostructured materials are of particular interest in enzyme kinetic study because of numerous benefits such as reactant exclusion and concentration, resulting from their biomolecule analogous geometry and favourable morphology. Nanoporous material are attracting more and more interest in applications such as biosensors because they can entrap reactants in the inner pores and confine the subsequent reactions in a nanometric space. Porous silicon has the capacity of material accommodation and signal transduction and thus, serves as a microreactor and sensor for sensing and kinetic studying simultaneously. Despite the complicated mechanisms affected by substrate nature, surface adsorption of enzyme and resulting conformational changes, and enzymatic reaction on the surfaces can be described by Michaelis-Menten relation on some conditions of assumption. As has been demonstrated above, the porous silicon based Bloch surface wave structure in this topic has the ability to detect proteases. Moreover, it can be utilized as a useful stage for kinetic study thanks to an open interface for easy sample administration and signal interrogation. A superficial sensing layer helps obviate mass transport problem in other structures relying on response in the whole multilayer medium. The reaction was discontinuously monitored by intermittently applying enzyme 143

solutions of certain concentration on the sensor and leaving for a period of time. When the scheduled time elapsed, the enzyme solution was removed the Bloch mode position in reflectivity spectra was recorded, indicating gelatin cleavage during the scheduled time. Another aliquot of enzyme solution could be applied on the sensor and the timing restarted. When the accumulated time was up, solution removal and mode position recording was repeated, until the total time length was reached. The dynamic data, including a series of Bloch mode positions and their corresponding time points, were fitted using an exponential formalism in an attempt to extract kinetic constants. Due to surface adsorption induced cleavage site limitation, it is reasonable to assume that on the sensor surface, substrate concentration is far lower than that supports the maximal

velocity, i.e. [S]«Km. Therefore, substrate consumption follows an exponential evolution:

ሾௌሿ೟ ௞೎ೌ೟ ሿ௧௢௧ݐሻ 5.3ܧൌሺെ ሾ ሾௌሿబ ௄ಾ

Where [S]t represents substrate concentrate at time t, [S]0 is the starting concentration of

the substrate while [E]tot stands for the total enzyme concentration. By fitting the

௏ reaction progress curve to the equation, Michaelis-Menten constant ೘ೌೣ, which best ௄೘ represents catalysis efficiency of an enzyme for a substrate, can be obtained in one experiment run. As the surface wave mode position is determined by the amount of gelatin immobilized on the sensor, the depletion of gelatin is readily translated into optical shift of the mode. Therefore optical measurement data can be put into the above equation for fitting. What is noteworthy with this approach is that it deals with the relative position of the Bloch mode position which is a dimensionless value, hence it can not only be used to extract initial rate without uncertainty caused by arbitrary timing in time taking for initial approximation, it also makes subjective estimation of the initial gelatin concentration involved in the reaction unnecessary. Figure 5.10 shows time courses of proteolytic reaction on two sensor chips and fitted curve in the presence of different levels of subtilisin.

144

Figure 5.10 Kinetic constant estimation via discontinuous monitoring of the reaction and fitting the data to the rate equation. Consistent values obtained in reaction at different protease levels reveal similar reaction mechanism for all protease concentrations.

Likewise, fitting of a reaction with subtilisin concentration of 0.007 mg/ml yielded a similar kinetic constant of 1.77×104r2600 M-1s-1. These results are in line with published substrate-dependent catalysis specificity values in a range of 102-106 M-1s-1

73,74 . Consistency of estimated Vmax/Km values at different concentrations is indicative of enzyme-catalysis mechanism in reactions at all protease levels in discussion. Kinetic monitoring using denatured subtilisin showed negligible proteolysis, as is shown in Figure 5.11. 0.005 mg/ml subtilisin was brought to boil in a water bath and kept in boiling water for 30 min. After cooling down to room temperature, a reaction was run

145 using denaturised protease instead of protease solution. Also shown in Figure 5.11 is dynamic observation of sensor response to PBS buffer.

Figure 5.11 Dynamic monitoring on protease (0.003mg/ml, red solid dots), PBS control (hollow squares) and deactivated protease (0.005 mg/ml, denaturized, hollow diamonds).

5.6 Conclusions and prospects The capability of sensitive and rapid detection of biological events has been demonstrated on the sensor platform fabricated and functionalized in chapter 4. The design of biosensor scaffold allows capitalization of all merits of porous silicon: large surface area and controllable network geometry. The engineered defect layer offers a biosensor platform enjoying multiple advantages as compared with classic porous silicon multilayer structures, such as open sensing space, spatially separate sample administration and signal interrogation regions, selective chemistry, tractable sensing reaction and specific response. Simple fabrication technique eliminates in-depth 146 inhomogeneities and mass transport problems. Well-defined surface chemistry ensures robust sensor surface and selective immobilization of biological entities in desirable locations for specific sensing interaction. Using surface chemistry developed on porous silicon Rugate filters, porous surface of the structure was stabilized through Si-C covalent bond formed by the hydrosilylation reaction. Subsequent conjugate chemistry enabled the coupling of low molecular weight gelatin in the outmost layer of the structure as the sensing element. The author demonstrated that with gelatin as an immobilized substrate, enzymatic catalyzed breakup of gelatin gel can be utilized to probe proteases. The exposure of the sensor to protease solution at room temperature yielded blue shifts as much as 31 nm in 20 min, which is quicker and larger than that observed in Rugate filter. Dose dependent proteolysis velocities, represented by the rate of Bloch mode shift, were used to quantitatively detect protease as a catalyst. Using subtilisin as a model protease, it has been shown that in a large range from sub micro-molar to nano-molar levels, the proteolysis velocities are linearly dependent on the concentration of subtilisin. The lowest detectable subtilisin concentration was 370 pM though it is possible to approach lower detection limit using a period of longer incubation. It has been demonstrated in this chapter that open sensing space and quick response provided by Bloch surface wave sensor is beneficial for kinetics study. In contrast to classic method based on initial rates which is reliant on the knowledge or subject to arbitrary assumption of substrate concentration, kinetic constants of enzyme can be estimated by fitting the time course curve to the rate equation. This is an advantageous way to estimate kinetic constant, in particular at the preliminary screening stage for a protease-substrate pair. It should be highlighted that, benefiting from mesoporous photonic elements, self-referencing capability of the Bloch surface wave structure is a very promising benefit which is worthy further investigation and exploitation. In the numerical calculation on the structure studied in this thesis, shown in Figure 5.12, the Bloch mode and band edge of the structure exhibit strikingly different response behaviors and it is obvious that these distinct responses can be explicitly attributed to the occurrence in 147 areas in the structure.The band edge mode has a weak dependence on changes to the top layer and this may be used to discriminate between optical shift arising from specific and non-specific adsorption. In Fig 5.12(a), we see clear distinction between the flat response of band-edge mode compared with the surface wave mode (dλ/dn ~295 nm / RIU) in the case that only the top layer is filled. In Figure 5.12(b), both modes give an approximately linear response when the refractive index change occurs throughout the entire structure if the porous matrix of whole structure is filled. These results suggest that the spectral shift of the surface wave mode due to targeted interaction events may be determined in the presence of a strong shift due to non-specific attachment by simply taking into account the shift of the band-edge mode, thus saving a lot of efforts in baseline drift correction. For example, in Figure 5.6(a), a 15 nm red shift in band-edge mode observed after proteolysis is associated with 27 nm red shift in the surface wave mode. Taking this into account in the observed 8 nm net blue shift we should expect that the enzyme-related shift should be a 35 nm blue shift, which was corroborated by the 31 nm blue shift observed in surface mode position after rinsing.

Figure 5.12 The predicted spectral response of the optical Bloch surface mode and Band-edge 148 mode to changes in the relative fraction of gelatin filling the pore space of the porous silicon layers: (a) changes occurring only in the top layer, and (b), changes occurring uniformly through the entire structure. The corresponding change in refractive index is displayed on the top axis.

Finally, as a superior sensor platform, an exciting potential of Bloch surface wave structure particularly deserving an exploration is regarding real-time sensing and kinetic study in a continuous manner which has been accomplished and widely in practice on SPR and numerous similar sensor types and prove successful in eliminating extra dependence of reaction on mass transport and the effect of fluctuation in temperature, pH and ionic strength75, 76. Sensitive, non-specific adsorption of the structure, as was shown in Figure 5.6 (a), and kinetic monitoring suggest the necessity of incorporation of fluidic system. To achieve this, some technical modification on the optical measurement setup will be needed. For example, in-coupling medium (coupling prism and refractive index matching oil) with higher refractive index have to be employed in order to achieve attenuated total reflection in the presence of aqueous solution (refractive index 1.33) rather than air (refractive index 1) as the extending medium. A preliminary experiment has shown that it is practicable to implement fluidic integration on porous silicon Bloch surface wave sensors.

References

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Chapter 6 Construction and characterisation of protein spaced porous silicon microcavity biosensors This chapter will cover a novel porous silicon based microcavity structure as a biosensor. The microcavity structure is constructed by assembling separately etched Bragg mirrors. The novelty of this structure is instead of all-porous silicon; a separately prepared protein layer is sandwiched in-between the Bragg mirrors supposed to form the microcavity. By optimising protein content when forming this layer by spin-coating, as well as other conditions, the resultant microcavity exhibits a resonant mode, defined by the thickness and refractive index of the protein layer. This resonant mode can be engineered in the near IR region. In principle, the central layer in microcavities fabricated in this way are accessible to both small and large molecules, thus they can be used in catalytic biosensors that cannot be realised in monolithic porous silicon microcavities. The optical thickness of the embedded protein layer is sensitive to external perturbations such as specific protease cleavage. In the attempt for protease detection, a number of technical constraints, such as, spurious signal due to baseline drift caused by hydration of protein layer, and vulnerability of the microcavity ensemble to aqueous environments were identified. It is envisaged that suitable surface chemistry for strengthened bonding between the protein layer and its surrounding Bragg reflectors is needed to improve the mechanical stability of the assembled structure for sensing applications. 6.1 Optical resonator/microcavity biosensors In the context of optical sensing, light-matter interactions can be intensified through localisation of light in a confined region so that the target molecules are seen. Field enhancement, as has been mentioned in the previous chapters, can be realised on a resonator (such as microspheres) where travelling waves detect the presence of

155 molecules or in a microcavity where more tightly confined standing waves detect the existence of foreign molecules in the multiple round trip of light. More specifically, a typical 1-D Fabry-Perot microcavity structure can be made by confining an optically active central layer in between two mirrors. The Figure 6.1 illustrates the configuration of a Fabry-Perot cavity.

Figure 6.1 Schematic of Fabry-Perot cavity formed by two reflectors (top). The bottom is a reflectivity spectrum indicating the dependence of resonance wavelength on the cavity separation.

From the perspective of optics, the optical thickness of the cavity, which is the product of its physical thickness and refractive index, is of a multiple integer of half 156 wavelengths at which light can propagate unimpeded throughout the whole structure. These microcavity structures such as Fabry-Perot interference filters are featured by a typical figure of merit known as the quality factor defined as Q = λ/∆λ, where λ is the of the resonance wavelength (peak wavelength), and ∆λ is the full width at half maximum (resonance peak width). Optical microcavities/resonators have been proposed as sensitive label-free optical biosensors because the resonant recirculation of light in these resonators allows the light to sample target molecules many more times. A range of resonance structures with varying Q-factors have been investigated for the purpose of biosensing applications1-4. In particular, a cavity enclosed by two multilayered dielectric mirrors (with reflectivity larger than 99%), known as distributed Bragg reflectors (DBRs), is the focus of this study. On top of the well known capability of light propagation control, photonic crystal microcavity devices come into focus as biosensor transducers because photonic crystals offer advantages of low absorptive loss, small sensing volume (as small as attoliters) and increased optical field intensity at the analyte5-9. 6.2 Porous silicon microcavities as label-free biosensors Porous silicon fabricated by anodisation of crystalline silicon is an easy way to obtain planar photonic crystals and represents a new avenue to build up versatile vehicles for biosensors: from perfectly ordered Bragg reflectors with discrete refractive modulation to Rugate filters featured by continuously varying refractive index profiles. Moreover, multilayer structures constituted by either regular periodicity or those with irregular components such as a λ/2 spacer on porous silicon are of particular interest to biosensor researchers4, 10-13 as porous silicon microcavity resonators are highly sensitive structures. For example, any slight change in the refractive index in the cavity layer will induce a change in the reflectivity spectrum. This makes porous silicon microcavity resonators an ideal host for sensor applications. For all the simplicity in fabricating, monolithic microcavities with a porous silicon central layer are not ideal for biosensor application because of the fact that while it is the central layer that is most sensitive to the stimulus, a blockage imposed by multilayered porous silicon with sharply varied porosities 157 prevents the materials of interest from accessing this region. As has been demonstrated in chapter 3, the possibility to create freestanding porous silicon thin film allows for the flexible choice of spacer material, opening up a new avenue to assemble hybrid structures by introducing foreign materials. Studies on fabrication of free-standing porous silicon films and their applications as sensors have been reported14-20. This chapter will describe a microcavity structure assembled from porous silicon Bragg reflectors in a manner similar to that discussed in chapter 2. 6.3 Design and fabrication of hybrid microcavity using gelatin as the spacer A multilayered porous silicon Bragg mirror is composed of alternating high and low refractive index layers (nH and nL). Reflectivity spectrum of a Bragg reflector is determined by three main parameters: periodicity, thickness of the layers and porosities

(i.e. refractive index contrast, nL / nH). The reflectivity of a Bragg mirror increases with the increase in the number of periods. By changing the thickness of the individual layers, the response of the multilayer mirror can be tuned. The thicknesses of the layers (H and

L respectively) are chosen so that nHdH = nLdL=λ/4. The increase in the thickness ratio

(dL/dH) shifts the reflectivity spectra toward the longer wavelength. When an active layer is placed in-between two highly reflecting Bragg mirrors, a 1-D microcavity results. It has been shown that such a 1-D structure based on mesoporous silicon can achieve sensitivity (∆λ/∆n) of 900 nm/RIU, depending on the extent filling factor of pores as a result of analyte infiltration21. In sensing applications, to address the restrictions associated with all porous silicon microcavities, the central layer has to be accessible to the analyte, and there is a need to constitute the central layer in another way so that it will be adequately exposed to the target analyte in sensing operations. One attempt made by Delouise et al demonstrated that by expanding the pore sizes of the mesoporous silicon, infiltration of large molecule such as glutathione-s-transferase (50 kDa)22. Although effective pore penetratration were achieved, there was dramatic degradation in the quality of the cavity structure, indicated by a worsening

158

Q-factor from 468 to 49. In order to improve the analyte infiltration, microcavities were also built up on macroporous silicon that allows ingress of large molecules with molecular weight of 150 kDa23. However, these structures are featured by low quality factor (Q=45) and thus, a significantly lower sensitivity than mesoporous structures24. A number of routes have been taken to form microcavities as hybrids with other materials such as polymers have been worked out25 and some of these innovations show improved thermodynamical stability and aptitude for sensing applications26. In these structures, however, the guest materials either act solely as a dielectric element of the microcavity or are utilized as an auxiliary to stabilise the reactive surface of porous silicon. What is proposed in this work is that a guest material that forms the central layer of a microcavity structure can serve as the bio-recognition element simultaneously. Conventional interferometric sensors rely on detecting the local refractive index changes that redefine the resonance conditions and thus shift the resonance wavelength. However, as can be seen from the Bragg conditions that the resonance wavelength position of a microcavity is not only determined by the refractive index of the cavity layer, resonance wavelength shift can also be caused by a change in the physical thickness of the cavity which is achievable and can be related to the events that cause such a change. In a porous silicon microcavity containing a protein layer as the spacer, proteolysis action by enzyme causes changes in both thickness (by homogeneous thinning of the protein layer) and refractive index (by inhomogeneous hollowing of the protein architecture). The shift of resonance wavelength can be accounted for by both factors:

οߣோ ൌʹο݊ȉ݀൅ʹ݊ȉο݀

Where ∆λR is the resonance wavelength, n and ∆n are refractive index of the cavity and its change respectively; d and ∆d are the cavity thickness and its change, respectively. A wider dynamic range can be envisaged in consideration of the fact that an optical shift is a result of multifactor modulation. Narrower transmission bands in microcavities (a few nm), than the reflection band in Rugate filters, can afford a better resolution of minor shifts, thus indicating potentially higher sensitivity to a small stimulus. A 159 microcavity which is substantially thinner than a Rugate filter (less than a μm versus a few μm) is favourable for molecule infiltration.

6.3.1 Device fabrication

As has been detailed in chapter 2 and specified in chapter 3, a hybrid microcavity is composed of two identical mesoporous silicon Bragg reflectors containing 6 periods high and low porosity layers. The thickness of high porosity layer was designed as 84 nm, etched for 1.7 s at a current of 220 mA, equivalent to a current density of 230 mA/cm2 while designed thickness of 136 nm for low porosity layer was a result of 2.6 s etching at 5 mA. On one of the mirrors, 50 mg/ml gelatin aqueous solution is spin- coated in order to form a protein layer whose thickness will ultimately determine the resonance wavelength of the microcavity. The other mirror is an electrochemically lifted off silicon wafer and reversed on the gelatin coated mirror. As a result of top mirror reversal, gelatin layer is embedded in the place of a spacer which otherwise is formed by two porous silicon layers with the same porosity in a monolithic structure. A low porosity layer is chosen on each side adjacent to the gelatin layer so that gelatin molecules will form an independent gelled entity rather than infiltrating into nanometric pores of 10 nm or below. An illustrative schematic of the microcavity fabrication is shown in Figure 6.2.

Figure 6.2 Illustration of the gelatin spaced microcavity fabrication process. 160

6.3.2 Designed cavity parameters

It is understood that the structural parameters of the component mirrors only dictate the width and position of the Bragg plateau. It is the optical thickness of the central layer that predominantly determines the position of the resonance wavelength. The thickness of high and low porosity layers were selected such that the central wavelength of the mirrors falls in the near IR region (700-1100), which is mostly studied band region for optical sensing. Considering the spectral range of the spectrometer used in the study, resonance wavelength λ0 is preferentially selected as 700- 900 nm. Accordingly, in consideration of the refractive index value of 1.534 for gelatin27, the thickness of gelatin layer is ideally in a range of 220-300 nm. 6.4 Characterisation of gelatin embedded microcavities

6.4.1 Measurement techniques

Microcavities were characterised using reflectivity measurement techniques with a white light beam at normal incidence, as detailed in chapter 2. As often, the thickness can be estimated from the scanning electron microscopic measurement. Figure 6.3 shows a SEM image of a gelatin spaced microcavity. Also shown is a reflectivity spectrum of the microcavity. The gelatin spaced microcavity has a quality factor of 165 - comparable with one formed by monolithic approach.

Figure 6.3 Left: scanning electron microscopic image of porous silicon microcavity with a 161 gelatin layer embedded between two identical 6 period Bragg mirrors. Right: reflectivity spectrum of the Bragg mirror (black line) and the microcavity (red line). The microcavity has a resonance dip at 825.5 nm and a line width of 5 nm, corresponding to a Q-factor of 165.1.

6.4.2 Spacer thickness

The thickness of the spacer is determined by the concentration of gelatin solution and the spinning parameters. To optimise the thickness of the spun film, a combination of gelatin concentration and spinning parameters has to be adopted and optimised. As a pre-test, gelatin spin-coating on bare silicon was carried out and the thicknesses of spun films were studied. The thicknesses of gelatin films on different conditions were extracted from reflectivity measurements at normal incidence with the help of a Matlab- based programme. With the increase in gelatin concentration, the spacer thickness increases (data from gelatin layer on silicon, not presented). The spacer will become thinner and more uniform with increased spinning speed. It was found that a gelatin concentration of 50 mg/ml and a ramp program of spinning resulted in suitable thicknesses with satisfactory uniformity. To achieve this, the spin speed ramp was programmed as: 500 rpm for 10 s, 1500 rpm for 10 s, 2500 rpm for 20 s, and 4000 rpm for 30 s. The porous silicon Bragg mirror was coated with gelatin using the above spinning conditions and a microcavity was subsequently assembled. By measuring the reflectivity of the microcavities, resonance wavelengths can be determined. Spacer thicknesses of the microcavities were derived from resonance relation demonstrated in figure 6.1. Resonance wavelength values and their variation between samples are an indicator of gelatin spacer thicknesses and their evenness. Figure 6.4a shows reflectivity spectra collected at different positions on one sample; the figure 6.4b exhibits variation in both resonance wavelength λ0 and calculated gelatin spacer thickness of the sample demonstrated in a). While 6.4 a and 6.4 b demonstrated spacer thickness homogeneity on a microcavity, he figure 6.4c shows sample-to-sample variation of 9 microcavities assembled in the same manner. There is a small variation among samples due to

162 fluctuation in fabrication conditions such as temperature while spatial inhomogeneity on one sample is less noticeable.

Figure 6.4 a): Reflectivity spectra exhibiting resonance wavelength values taken at different position (indicated in the inset) on one microcavity sample; b): numeral values and variation of resonance wavelength (blue line and the calculated thickness (red line) from 9 readouts demonstrated in a). a) and b) results obtained on one microcavity sample (a is graph and be pesents numbers of both lambda and cavity thickness). c) demonstrates the fabrication reproducibility by measuring 9 microcavities and obtaining the average cavity thicknesses in a way used by b) (calculting the cavity thickness from optical measurement). Error bars represent standard deviation of at least 5 measurements.

6.4.3 Spacer surface roughness

A well-defined cavity mode is guaranteed by interfaces in porous silicon bulk structures and that of spun gelatin. While sharp interfaces between porous silicon layers are a result of etching condition control and optimisation, the smoothness of the spun gelatin

163 surface is a key contributor to the narrow resonance band. Smoothness of the films was inspected using optical microscopy. Detailed surface profiling was conducted on Digital Instruments Nanoscope atomic force microscopy (AFM) under tapping mode. Figure 6.5 shows the surface roughness of spin-coated gelatin film on a porous silicon Bragg reflector.

Figure 6.5 Atomic force microscopic images of gelatin layer spun on a porous silicon Bragg 164 mirror indicating the mean roughness of the spun surface.

As can be seen from the AFM image, the root mean square roughness of the scanned area is 0.366 nm (upper image) with maximal peaks and pits size within 4 nm (bottom image). Smooth surface with low level of roughness is also corroborated by narrow resonance wavelength in the optical reflection measurement (Figure 6.3). 6.5 The attempts towards protease detection with gelatin spaced microcavities The microcavity structure established as above contains gelatin layer as the spacer. As has been known, the resonance in a microcavity is governed by the Bragg conditions: ɉ ଴ ൌ݊݀ ʹ݉

Where λ0 is resonance wavelength, m is the spectral order, n and d is the refractive index and the thickness of the spacer, respectively. It is obvious from the Bragg relation that optical properties of a microcavity are sensitively governed by the optical thickness of the spacer. A minor change in the local refractive index resulting from the optical field interaction and the subsequent polarization of biomolecules appearing in the cavity will lead to a shift in the resonance wavelength to the longer wavelength (red shift). Red shift in resonance wavelength can also be triggered by the increases in the physical thickness of the central layer. On the other hand, reduced refractive or thickness due to removal of biomolecules or structural disruption will be detected as a blue shift in the resonance wavelength. A typical example of such a blue-shift sensing modality is protease detection based on immobilized protein, as was demonstrated in chapter 5. If a protein layer as an optical component is cleaved by protease, both physical thickness and the local refractive index will decline. In the hybrid gelatin/structure in discussion, such a reduction in optical thickness of the central layer of the microcavity will lead to a spectral shift to the shorter wavelength. However, as will be demonstrated in the following section, excessive cleavage in the microcavity may lead to collapse of microcavity structure as a consequence of the device falling apart. Physical instability of 165 devices is a concern in sensing operation and will need to be addressed in the ongoing study.

6.5.1 Analyte sample administration

One of the most prominent differences of gelatin spaced microcavity as a sensing device is that unlike most recent reports, which are based on changes in optical or electrical properties of porous network through pore-to pore diffusion of analyte, target analytes access the central layer from the side of the structure. This way of analyte targeting not only eliminates the problem of mass transport associated with monolithic microcavities, but in principle, it also implies a higher sensitivity as it is possible to exclusively target the central layer. The highest sensitivity can be achieved when central layer is selectively attacked as illustrated by the comparison in Figure 6.6.

Figure 6.6 Comparison of sample administration pathways between the monolithic (left) and the hybrid (right) microcavities.

The microcavity structures were exposed to protease solution in a number of ways. One consideration is to impregnate small piece of filter paper with the solution such that solution is delivered to the sensor and maintain liquid status during the cleavage reaction. The best way, though, is to spot an aliquot of solution onto the sensor chip or immerse the sensor in the solution.

6.5.2 Spatial incidence of probing light 166

White light reflectivity measurements of the optical resonator are typically performed at normal incidence. To avoid the interference from blockage and scattering of liquid film with the incident light, a number of attempts have been made, as are illustrated in the Figure 6.7.

Figure 6.7 Two typical ways sample solution is delivered. While it is hard to avoid the disruption of signal reading due to the interference from liquid membrane in the horizontal configuration (left), vertical configuration (right) hardly yields responses due to the hydraulic restriction.

One problem with porous silicon optical sensors is that in most cases devices are attached to their native substrate, limiting optical characterisation technique to reflection only where air acts as both incident and reflected medium for light. Convergence of light pathway and analyte solution administration inflicts problems of lost or convoluted spectra and therefore, less reliable results. Particularly problematic is the formation of a meniscus on the surface of the sample which modified the reflected beam path and leads to a misalignment of the beam with the coupling optics. A new design, shown in the Figure 6.8, utilizes the symmetry of the microcavity structure to separate signal interrogation from sample administration space. A transparent material is used to support the microcavity so that light is incident from underneath the structure while sample solution can be applied from the top of the sensors. The reflected light is collected using the same setup with an objective aligned under the sensor. This way, 167 signal collection is not disrupted and continuous monitoring can be conducted.

Figure 6.8 Optical responses obtained from silicon-supported (left) and glass-supported microcavities. Independent optical interrogation space rules out the signal disruption caused by scattering at sample solution surface.

6.5.3 Responses to protease

In the horizontal configuration illustrated in the Figure 6.7 (left), when the solution spreads on the sensor chip, the probing light is scattered by the liquid layer rather than being incident on the sensor. As a consequence, the reflectivity spectrum is distorted or diminished and becomes obscured. Total immersion of the sensor chip in solution containing cuvette can ensure inherent light incidence as was the case in Rugate filter sensor; it will cause integration of the intrinsically less stable structure constructed by simple assembly. Vertical configuration (Figure 6.7 right), eliminated the loss of signal as the sensor chip dips in the enzyme solution. It is interesting to notice during the

168 continuous monitoring that the cavity mode exhibits oscillation behaviour in a wavelength range to the longer wavelength, possibly suggesting a reversible infiltration of the solution into gel network driven by capillary condensation. When the solution is removed, the mode returns to the original position after the sensor surface dries up, implying unchanged local refractive index after the enzyme action. However, the mode evolution always starts with a red shift upon the application of either enzyme or PBS buffer. After the enzyme action, more often than not, a net red shift instead of blue shift, as anticipated, is observed. Figure 6.9 is an example that shows red shifts on both enzyme and PBS exposure.

Figure 6.9 Optical responses of a microcavity structure to 0.1 mg/ml subtilisin and PBS buffer respectively. Net red shifts in are attributed to swelling of gelatin, accumulation and retention of cleavage debris.

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The mixed results can be attributed to the following causes: a) Swelling of the gelatin gel. Hydration induced swelling is a phenomena for hydrogels including gelatin. Swelling of gelatin causes changes in the local refractive index and thus, shifts of the optical features28. Visual colorimetric detection of swelling behaviour has been demonstrated on porous silicon microcavities29. b) Degradation of the structure due to surface oxidation. c) Accumulation and re-adsorption of cleavage products (short peptide fragments and amino acids) in the gel network. d) Infiltration of small molecules generated in the enzyme reaction into the pores in the vicinity. e) Disintegration of the microcavity structure. Disintegration of the assembled gelatin microcavities was observed when the structure was immersed in a PBS buffer. As a consequence of movement and displacement of the top mirror caused by dissolution of gelatin in aqueous solution, it is conceivable that during the sensor incubation in solution, the top mirror was washed off, moved and resettled onto the partially cleaved gelatin film. Due to the lateral inhomogeneity of both the porous silicon mirror and the gelatin layer, the readout of the “new” cavity is different from that of the original one, either to the longer or shorter side of the as fabricated cavity in the spectra. Displacement of the top mirror may misshape the microcavity structure and result in the attenuation of reflectivity, distortion of spectra, or disappearance of cavity features which have been seen in experiments, particularly for the horizontal measurement configuration. Due to the lateral inhomogeneity across the device, false positive response can be observed as a result of resettlement of top mirror instead of gelatin cleavage. On some occasions, a significant blue shift does appear for PBS control, suggesting either gelatine dissolution or displacement of the top mirror (cavity mode variation across one sample can be up to 20 nm, see Figure 6.4). 6.6 Conclusion and future work Embedding protein between Bragg mirrors is an idea extended from the monolithic structure in an attempt to eliminate the parasitic restriction facing microcavity sensors. 170

Protein not only forms a component layer of the microcavity but is assigned a role as a specific recognition element for proteases. Fabrication of high quality microcavities containing gelatin as the spacer has been demonstrated using spin-coating technique and porous silicon thin film flipping. Impact of gelatin concentration, spinning speed and spinning programme on the spacer thickness and the roughness of the gelatin film have been studied and discussed. Device fabrication exhibits good reproducibility. Optical measurement techniques for biosensing operation are compared and a new configuration is proposed to spatially separate sample administration and optical interrogation so as to eliminate disruption of measurement and the subsequent uncertainty in measurement. Despite the simplicity of fabrication, some critical restraints related to the devices have been identified. In order to obtain robust results, the sensor has to be chemically stabilised against oxidative degradation. Modification is also needed to prevent non- specific adsorption on the sensor surface. More importantly, comprehensive surface chemistry is needed to maintain the integrity of the structure For example, as has been shown in the previous chapter, gelatin can be anchored onto the carboxylic acid O modified bottom mirror via amide bonding ( CNH) and the top mirror can also tethered down using the same mechanism. The challenge is the multistep modification and manipulation of the brittle free-standing top mirror. Figure 6.9 illustrates the envisaged chemical modification for mechanical stability improvement.

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Figure 6.10 Envisaged microcavity structure with improved surface stability, anti-fouling capability and mechanical integrity, resulting from surface modification and functionalisation.

It is hopeful that once the porous silicon building blocks are chemically stabilised and functionalised properly, a sensitive and robust microcavity biosensor platform can be established.

References

1. Mandal, S.; Goddard, J. M.; Erickson, D., A multiplexed optofluidic biomolecular sensor for low mass detection. Lab on a Chip 2009, 9, (20), 2924-2932. 2. Vollmer, F., Taking detection to the limit. BIF Futura 2005, 20, 239-244. 3. Washburn, A. L.; Gunn, L. C.; Bailey, R. C., Label-Free Quantitation of a Cancer Biomarker in Complex Media Using Silicon Photonic Microring Resonators. 172

Analytical Chemistry 2009, 81, (22), 9499-9506. 4. Palestino, G.; Legros, R.; Agarwal, V.; Pérez, E.; Gergely, C., Functionalization of nanostructured porous silicon microcavities for glucose oxidase detection. Sensors and Actuators B: Chemical 2008, 135, (1), 27-34. 5. Burr, G. W.; Chow, E.; Mirkarimi, L. W.; Sigalas, M.; Grot, A., Photonic crystal microcavities as ultracompact film-thickness monitors for biosensing. Integrated Photonics Research and Applications/Nanophotonics for Information Systems 2005. 6. Krioukov, E.; Klunder, D. J. W.; Driessen, A.; Otto, C.; Greve, J., Refractive index sensing using an integrated optical microcavity. Optics Letters 2002, 7, 512–514. 7. Boyd, R. W.; Heebner, J. E., Sensitive disk resonator photonic biosensor. Applied Optics 2001, 40, (31), 5742-5747. 8. Ksendzov, A.; Lin, Y., Integrated optics ring-resonator sensors for protein detection. Optics letters 2005, 30, (24), 3344-3346. 9. Fauchet, P. M.; Rothberg, L. J.; Miller, B. L., Silicon-based biosensors for rapid pathogen detection. Abstracts of Papers, 225th ACS National Meeting, New Orleans, LA, United States, March 23-27, 2003 2003, IEC-244. 10. Chan, S.; Li, Y.; Rothberg, L. J.; Miller, B. L.; Fauchet, P. M., Nanoscale silicon microcavities for biosensing. Materials Science & Engineering, C: Biomimetic and Supramolecular Systems 2001, C15, (1-2), 277-282. 11. Torres-Costa, V.; Agullo-Rueda, F.; Martin-Palma, R. J.; Martinez-Duart, J. M., Porous silicon optical devices for sensing applications. Optical Materials (Amsterdam, Netherlands) 2005, 27, (5), 1084-1087. 12. De Stefano, L.; Moretti, L.; Rendina, I.; Rossi, A. M., Time-resolved sensing of chemical species in porous silicon optical microcavity. Sensors and Actuators, B: Chemical 2004, B100, (1-2), 168-172. 13. Ouyang, H.; DeLouise, L. A.; Miller, B. L.; Fauchet, P. M., Label-Free Quantitative Detection of Protein Using Macroporous Silicon Photonic Bandgap Biosensors. Analytical Chemistry 2007, 79, (4), 1502-1506. 14. M.Ghulinyan, C. J. O., G.Bometti, Z.Gaburro, and L.Pavesi, free-standing porous silicon single and multiple optical cavities. Journal of Applied Physics 2003, 93, (12), 9724-9727. 15. O Garel, C. B., E Dufour-Gergam, A Bosseboeuf, B Belier, V Mathet and F Verjus, Fabrication of free-standing porous silicon microstructures. J.Micromech.Microeng. 2007, 17, S164-S167. 16. Tokranova, N.; Xu, B.; Castracane, J., Fabrication of flexible one-dimensional porous silicon Photonic Band-Gap structures. Materials Research Society Symposium Proceedings 2004, 797, (Engineered Porosity for Microphonics and Plasmonics), 3-8. 17. Baratto, C.; Faglia, G.; Comini, E.; Sberveglieri, G.; Taroni, A.; La Ferrara, V.; Quercia, L.; Di Francia, G., A novel porous silicon sensor for detection of sub-ppm NO2 concentrations. Sensors and Actuators B: Chemical 2001, 77, (1-2), 62-66. 18. DeLouise, L. A.; Fauchet, P. M.; Miller, B. L.; Pentland, A. A., Hydrogel- supported optical-microcavity sensors. Advanced Materials (Weinheim, Germany) 2005, 17, (18), 2199-2203.

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19. DeLouise, L. A., Smart bandage - a hydrogel supported optical microcavity sensor. NSTI Nanotech 2005, NSTI Nanotechnology Conference and Trade Show, Anaheim, CA, United States, May 8-12, 2005 2005, 1, 51-54. 20. Martin, M.; Taleb Bendiab, C.; Massif, L.; Palestino, G.; Agarwal, V.; Cuisinier, F.; Gergely, C., Matrix metalloproteinase sensing via porous silicon microcavity devices functionalized with human antibodies. physica status solidi (c) 2010, 1-5. 21. DeLouise, L. A.; Kou, P. M.; Miller, B. L., Cross-Correlation of Optical Microcavity Biosensor Response with Immobilized Enzyme Activity. Insights into Biosensor Sensitivity. Analytical Chemistry 2005, 77, (10), 3222-3230. 22. DeLouise, L. A.; Miller, B. L., Optimization of mesoporous silicon microcavities for proteomic sensing. Materials Research Society Symposium Proceedings 2004, 782, (Micro- and Nanosystems), 117-123. 23. Ouyang, H.; Christophersen, M.; Viard, R.; Miller, B. L.; Fauchet, P. M., Macroporous Silicon Microcavities for Macromolecule Detection. Advanced Functional Materials 2005, 15, (11), 1851-1859. 24. Ouyang, H.; Striemer, C. C.; Fauchet, P. M., Quantitative analysis of the sensitivity of porous silicon optical biosensors. Applied Physics Letters 2006, 88, (16), 163108-3. 25. Sychev, F. Y.; Razdolski, I. E.; Murzina, T. V.; Aktsipetrov, O. A.; Trifonov, T.; Cheylan, S., Vertical hybrid microcavity based on a polymer layer sandwiched between porous silicon photonic crystals. Applied Physics Letters 2009, 95, (16), 163301- 163301-3. 26. De Stefano, L.; Rotiroti, L.; De Tommasi, E.; Rea, I.; Rendina, I.; Canciello, M.; Maglio, G.; Palumbo, R., Hybrid polymer-porous silicon photonic crystals for optical sensing. Journal of Applied Physics 2009, 106, (2), 023109-023109-5. 27. Martínez-Antón, J. C.; Bernabeu, E., Spectrogoniometry and the WANTED method for thickness and refractive index determination. Thin Solid Films 1998, 313- 314, 85-89. 28. Segal, E.; Perelman, L. A.; Cunin, F.; Di Renzo, F.; Devoisselle, J. M.; Li, Y. Y.; Sailor, M. J., Confinement of Thermoresponsive Hydrogels in Nanostructured Porous Silicon Dioxide Templates. Advanced Functional Materials 2007, 17, (7), 1153-1162. 29. Lisa M. Bonanno, L. A. D. Optical Detection of Polyacrylamide Swelling Behavior in Porous Silicon Sensor. Mat. Res. Soc. Symp. Proc., 2008; 2008; pp 1133- AA01-05.

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Chapter 7 General conclusion

7.1 Summary Throughout this thesis a number of important and novel approaches to extending the optical functionality of porous silicon multi-layered structures, through a range of different hybridization schemes, have been demonstrated. Whilst these methods have been directed towards the development high sensitivity optical biosensing, they are more generally applicable to a broad range of applications where the optical properties of porous silicon are employed. This chapter will conclude the thesis with a summary of the key findings from this work and provide an outlook for future directions of hybrid porous silicon photonics. In the first part of the study the possibility of assembling planar optical components to form new photonic structures using biomolecular directed assembly was explored. Here the highly specific, and strong, binding affinity of naturally occurring conjugate molecules biotin and streptavidin was exploited. The approach involved coating (via physisorption) freestanding porous silicon components with biotin-BSA. The complementary molecules (streptavidin) built in quantum dots serve as linkers in immobilizing quantum dots and then bringing the two components in contact under ambient conditions. In this way albeit was possible to demonstrate the construction of optical microcavities from separately constructed Bragg reflectors without modifying the optical properties or introducing significant optical losses compared with monolithically grown structures. Part of the benefit of the biomolecular-directed approach is that it allows for the combination of traditionally dispirit materials without the restrictive epitaxial growth conditions. As the binding layer in this approach is essentially amorphous it conforms to the surface of the mating pairs without the need for lattice-matching. As an example II-VI semiconductor colloidal quantum dots were incorporated into a resonant silicon photonic structure and observed a corresponding change in the light emission properties

175 of the quantum dots. As a demonstration of the flexibility of the approach quantum dots with different emission spectra ranging from the visible to near infrared regime were incorporated. The technique allows for free choice of different quantum dots for different spectral bands. Moreover, it is possible to tune the emission band of a single device using the surface and morphological properties of the porous silicon. By introducing glycerol/water mixture, modified emission with embedded 800 nm quantum dots was tuned in a range of 20 nm, i.e., emission can be switched on and off between to narrow band 20 nm apart. Another advantage of the hybridization is that porous silicon structures may be assembled on a range of different substrates. This opens the possibility of new methods of sensing. In chapter 4, it was demonstrated that a minor variation in the etching parameters, a porous silicon Bragg reflector can be made to sustain surface waves which have strong implications in sensing. The structure was transferred and bonded to a transparent substrate, which enabled the use of allowed prism coupling for coupling and monitoring of these evanescent modes. To protect the reactive porous silicon surface from degradation and render the structure function for sensing applications, well documented surface chemistry was implemented. Numerical modelling was employed to verify the optimised structure showed excellent agreement between experimental results and theoretical prediction. To demonstrate the sensing potential of the Bloch surface wave structure, the device was interfaced with gelatin as an immobilized substrate. Enzymatic catalyzed degradation of the gelatin was utilized to probe protease activity. Room temperature exposure of the sensor to a protease solution at yielded an appreciable blue shift in 20 min. Dose dependent proteolysis velocities, represented by the rate of Bloch mode shift, were used to prove the potential capability of the structure to quantitatively detect protease. Open sensing space and quick response provided by Bloch surface wave sensor has been shown beneficial for kinetics study. The use of the other spectral features, such as the photonic band edge mode allowed, for simultaneous detection of nonspecific binding of small molecules and ionic species.

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In chapter 6, a hybrid microcavity structure was created by sandwiching a protein layer in-between two identical Bragg mirrors. Protein layer was formed on the bottom Bragg mirror using spin-coating technique. The microcavity structure constructed in this way has the quality factor comparable with monolithically formed microcavities and therefore has the potential to be used as biosensors. However, the attempt to detect protease activity using the gelatin embedded microcavity as a biosensor has been confronted by a series of technique problems such as structural instability.. Some technical measures were taken to avoid signal loss or convolution, however, it was found that in order to improve the stability of the structure some fundamental solution will be needed.

7.2 Outlook

7.2.1 This thesis conceptually demonstrates that, formation of hybrid structure at nanometric scale can be achieved by biomolecule assisted assembly. More detailed study of the integration of different materials at nanoscale will be critical. To exploit the specificity of biomolecules, surface modification will be needed to render the surface versatile and reliable functionalities. This will also lead to improving the integrity and robustness of the hybridization process.

7.2.2 As a possible extension of the study undertaken on the surface wave structure proposed in this thesis, operational benefits resulting from structure such as potential role of band edge as internal reference and amenability to be integrated to microfluidic technique will need further investigation.

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Appendix: List of publications A1: Journal publications

Hong Qiao, Bin Guan, Till Bocking, Michael Gal, J. Justin Gooding and Peter J Reece, Optical properties of II-V colloidal quantum dot doped porous silicon microcavities, Appl. Phys. Lett. 96, 161106 (2010)

Hong Qiao, Bin Guan, J. Justin Gooding, and Peter J Reece, Protease detection using porous silicon based Bloch surface wave optical biosensor, Optics Express, Vol. 18, No.14, 15174-15182 (2010)

Anh Pham, Hong Qiao, Bin Guan, Michael Gal, J. Justin Gooding, and Peter J. Reece, Optical bistability in mesoporous silicon microcavity resonators, JOURNAL OF APPLIED PHYSICS 109, 093113 (2011)

A2: Conference proceedings

Hong Qiao, Michael Gal, J. Justin Gooding, and Peter J Reece, Incorporation of colloidal quantum dots into silicon photonic structures, accepted for the Proceedings of ICONN 2010

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