Magnéli Phase Tio2 and Their Thermoelectric Properties

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Magnéli phase TiO2 and their thermoelectric properties

Wen Lee

A thesis in fulfilment of the requirements for the degree of

Master of Science

School of Materials Science and Engineering

Faculty of Science

February 2020

Thesis/Dissertation Sheet

Surname/Family Name : Lee

Given Name/s : Wen

Abbreviation for degree as give in the University calendar : M.Eng

Faculty : Science

School : Materials Science

Thesis Title : Magnéli phase TiO2 and their thermoelectric properties

Abstract 350 words maximum:

With the global temperature rising due to the Greenhouse effect at the same time, the search for clean, efficient, renewable energy source is of utmost importance. Thermoelectric materials have been receiving attention due to their potential application in converting waste heat into electrical energy. Metal oxides has always been an important research focus in the field of thermoelectrics for their low production cost and availability. A series of phases exist in the Ti-O system that has higher electrical conductivity than TiO2 called the Magnéli phases. These phases can be formed with simple reduction reaction, usually by carbon or hydrogen.

In this work, Magnéli phase TiO2 was investigated for thermoelectric applications. TiO2-x pellets were made with the hydrogen reduction method and the carbon reduction method. XRD and TGA results were cross analysed to determine the exact phase and oxygen content of the sample pellets. The results show that reducing TiO2 have drastically increased its electrical conductivity by introducing free electrons, transforming the insulating TiO2 into a n-type semi-conductor. While lattice thermal conduction dominated, the thermal conductivity was not dependent on the oxygen content.

Magnéli phase TiO2 was also fabricated with the carbon reduction technique. Graphite was embedded in pellets before being reduced at high temperature in an inert atmosphere. XRD analysis was done for phase characterization and to ensure no residual graphite was present. Electrical conductivity, Seebeck coefficient and thermal diffusivity measurements are done to estimate ZT.

Moreover, the electrochemistry property of Magnéli phase TiO2 was investigated by employing the Linear Scanning Voltammetry for Hydrogen Evolution Reaction at various scanning rates. The polarization curves and Tafel plots were plotted.

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Acknowledgment

I would like to express my sincere gratitude and appreciation to my supervisor Prof.

Sean Li, for his guidance and support towards completion of this work. He gave constant supervision for my experiments, result discussions, and manuscript preparation.

Grateful acknowledgements are to our technical staffs and lab managers: Dr. Bill Joe,

Dr. Rahmat Kartono, Dr George Yang and Dr. Thiam Teck Tan for their support of the measurements and practical advices. Appreciations to their insightful technical comments and continuous encouragements as well.

Special thanks also goes to Yichen Liu, who helped with many of my experiments and planning, and has given me guidance throughout the completion of this work. I would also like to acknowledge everyone in Prof. Sean Li’s group for their support.

Sincere thanks to Prof. David Waite and Changyong Zhang from the Water Research

Centre for conducting the HER measurements.

Lastly, I would like to thank my family – my brother Jerry and my parents for their love, understanding and support throughout my work.

Abstract

With the global temperature rising due to the Greenhouse effect at the same time, the search for clean, efficient, renewable energy source is of utmost importance.

Thermoelectric materials have been receiving attention due to their potential application in converting waste heat into electrical energy. Metal oxides has always been am important research focus in the field of thermoelectrics for their low production cost and availability. A series of phases exist in the Ti-O system that has higher electrical conductivity than TiO2 called the Magnéli phases. These phases can be formed with simple reduction reaction, usually by carbon or hydrogen.

In this work, Magnéli phase TiO2 was investigated for thermoelectric applications. TiO2- x pellets were made with the hydrogen reduction method and the carbon reduction method. XRD and TGA results were cross analysed to determine the exact phase and oxygen content of the sample pellets. The results show that reducing TiO2 have drastically increased its electrical conductivity by introducing free electrons, transforming the insulating TiO2 into a n-type semi-conductor. While lattice thermal conduction dominated, the thermal conductivity was not dependent on the oxygen content.

Table of Contents Acknowledgment ...... i Abstract ...... iii Table of Contents ...... v List of Figures ...... viii List of Tables ...... xi List of Equations ...... xii Chapter 1. Introduction ...... 1 1.1 Motivation ...... 1 Chapter 2. Literature Review ...... 2 2.1 The Thermoelectric effect ...... 2 2.1.1 Thermoelectric efficiency ...... 3 2.1.2 Thermal conductivity ...... 5 2.1.3 Seebeck coefficient ...... 6 2.1.4 Ways to improve ZT...... 6 2.2 The Titanium-Oxygen system ...... 8

2.2.1 TiO2 Structures ...... 9

2.2.2 Reduced TiO2 ...... 10 2.2.2.1 Electrical conductivity ...... 12 2.3 Synthesis method ...... 13 2.3.1 Carbothermic reduction...... 13 2.3.2 Hydrogen reduction...... 14 2.3.3 Metallothermic reduction ...... 15 2.4 Applications...... 18 2.5 Hydrogen Evolution Reaction ...... 20 2.5.1 Theory ...... 21

2.5.2 Magnéli phase TiO2 as cathode for HER ...... 22 Chapter 3. Experimental Methods ...... 24 3.1. Fabrication methods ...... 24 3.1.1. Materials...... 24

3.1.2. Hydrogen reduction...... 24 3.1.2.1. Pellet preparation ...... 25 3.1.2.2. Reduction parameters ...... 26 3.1.3. Carbothermic reduction...... 27 3.1.3.1. Spark Plasma Sintering ...... 28 3.2. Characterization techniques ...... 29 3.2.1. X-ray diffraction...... 29 3.2.2. Optical microscopy ...... 30 3.2.3. Scanning Electron Microscopy ...... 31 3.2.4. Seebeck coefficient and electrical resistivity analysis ...... 31 3.2.5. Thermogravimetric analysis ...... 32 3.2.6. Thermal diffusivity analysis ...... 33 3.2.7. Differential scanning calorimeter analysis ...... 35 3.2.8. Density measurements ...... 36 3.2.9. Carrier concentration and mobility measurements ...... 37 3.2.10. UV-vis Spectroscopy ...... 37 3.2.11. Linear Sweep Voltammetry ...... 38

Chapter 4. Controlling the Oxygen Level of Magnéli Phase TiO2 with Hydrogen Reduction Technology ...... 39 4.1. Introduction ...... 39 4.2. Experimental procedure ...... 41 4.3. Results and discussion ...... 42 4.3.1. Establishing the parameters ...... 42 4.3.2. Phase identification ...... 48 4.3.3. Thermoelectric properties ...... 55 4.4. Summary ...... 65

Chapter 5. Controlling the Oxygen Level of Magnéli Phase TiO2 with Carbon Reduction Technology ...... 66 5.1. Introduction ...... 66 5.2. Experimental procedure ...... 67

5.3. Results and discussion ...... 70 5.3.1. Phase identification ...... 70 5.3.2. Thermoelectric properties ...... 73 5.4. Summary ...... 80

Chapter 6. Magnéli Phase TiO2 as Cathode Material in HER ...... 81 6.1. Introduction ...... 81 6.2. Experimental Procedure ...... 82 6.3. Results and Discussion ...... 83 6.3.1. Polarization curves ...... 83 6.3.2. Tafel plots ...... 87 6.4. Summary ...... 90 Chapter 7. Conclusion and Future Works ...... 91 REFERENCES...... 95

List of Figures

Figure 2-1 Maximizing figure of merit ZT through carrier concentration. Trends were

[1] modeled from Bi2Te3 ...... 4

Figure 2-2 Disorder in the unit cell. a.) skutterudites[21], b.) clathrates[23] ...... 7

[1] Figure 2-3 Separating the conduction routes . a.)NaxCoO2, b.) CaxYb1-xZn2Sb2 ...... 8

Figure 2-4. Bulk structures of rutile and anatase[2]...... 9

Figure 2-5. Phase diagram of the Ti-O system[3] ...... 11

[34] Figure 2-6 Different orientations of TiO2 octahedra ...... 12

[43] Figure 2-7 Electrical conductivity of Magnéli phase TiO2 ...... 13

[48] Figure 2-8 Equilibrium phases for the hydrogen reduction of TiO2 ...... 15

Figure 3-1 Diagram of spark plasma sintering plant[74]...... 28

Figure 3-2 Principles of X-ray Diffraction[76] ...... 29

Figure 3-3 A schematic drawing of an optical microscope[77] ...... 30

Figure 3-4 Schematic of the ZEM-3 setup[78]...... 32

Figure 3-5 Schematic diagram of the thermogravimetric analysis system[80] ...... 33

Figure 3-6 Schematic of the LFA [82]...... 35

Figure 3-7 Schematic diagram of a DSC furnace[83] ...... 36

Figure 3-8 Schematic of a pycnometer[84] ...... 37

Figure 3-9 Schematic of typical LSV set-up ...... 39

Figure 4-1 Weight changes in the oxygen loading annealing processes at a) 1200°C and b) 1300°C ...... 43

Figure 4-2 XRD spectra of samples from Batch 1 ...... 46

Figure 4-3 Optical Microscope images of samples from Batch 1 with different oxygen deficiencies (2-x). a) 1.812, b) 1.852, c) 1.876, and d)1.943 ...... 47

Figure 4-4 Weight change during heating for samples from Batch 2 ...... 48

Figure 4-5 XRD spectra of Batch 2 samples...... 51

Figure 4-6 Cross-section of sample1.910 close to the surface...... 53

Figure 4-7 SEM image of the x = 1.910 sample ...... 53

Figure 4-8 Optical Microscope images of samples from Batch 2 with different oxygen deficiencies (2-x)...... 54

Figure 4-9 The temperature dependence of resistivity for Batch 2 ...... 56

Figure 4-10 Resistivity versus oxygen content at room temperature ...... 56

Figure 4-11 Kubelka-Munk function versus energy plot for TiO2-x samples ...... 57

Figure 4-12 The temperature dependence of the Seebeck coefficient for Batch 2 ...... 59

Figure 4-13 a) carrier concentration and b) carrier mobility of the samples from Batch 2 versus oxygen deficiency ...... 60

Figure 4-14 The temperature dependence of total thermal conductivity for Batch 2 ..... 62

Figure 4-15 The temperature dependence of a) Carrier thermal conductivity and b)

Lattice thermal conductivity ...... 63

Figure 4-16 The temperature dependence of ZT...... 64

Figure 5-1 XRD spectra of SPS samples ...... 71

Figure 5-2 OM images of SPS samples a) SPS-1, b) SPS-2 graphite was highlighted in red...... 72

Figure 5-3 The temperature dependence of resistivity for SPS samples. Data for

TiO1.77 was reproduced from ref [25] ...... 73

Figure 5-4 The temperature dependence of the Seebeck coefficient for SPS samples.

Data for TiO1.77 was reproduced from ref [25] ...... 74

Figure 5-5 The temperature dependence of thermal conductivity for SPS samples. Data for TiO1.77 was reproduced from ref [25] ...... 75

Figure 5-6 The temperature dependence of a) Carrier thermal conductivity and b) lattice thermal conductivity for SPS samples. Data for TiO1.77 was reproduced from ref [25] . 78

Figure 5-7 The temperature dependence of ZT for SPS samples. Data for TiO1.77 was reproduced from ref [25] ...... 79

Figure 6-1 Polarization curve for Magnéli phase TiO2 samples scanned at 2 mV/sec ... 85

Figure 6-2 Polarization curve for Magnéli phase TiO2 samples scanned at 10 mV/sec . 85

Figure 6-3 Polarization curve for Magnéli phase TiO2 samples scanned at 50 mV/sec . 86

Figure 6-4 Tafel slopes for Magnéli phase TiO2 samples scanned at 10 mV/sec ...... 88

Figure 6-5 Tafel slopes for Magnéli phase TiO2 samples scanned at 50 mV/sec ...... 88

List of Tables

Table 2-1 Reduction Parameters for various studies ...... 18

Table 3-1 Pressing parameters for the hydraulic press ...... 25

Table 3-2 Reduction parameters for batch 1 ...... 26

Table 3-3 Reduction parameters for batch 2 ...... 27

Table 4-1 Calculated oxygen deficiency for Batch 1 ...... 44

Table 4-2 A list of phases analyzed from the XRD spectra versus calculated value ...... 46

Table 4-3 Calculated oxygen deficiency for Batch 2 in ascending order ...... 48

Table 4-4 A list of phases analyzed from the XRD spectra versus calculated value ...... 52

Table 5-1 A list of target n value with % graphite and reduction parameters ...... 68

Table 5-2 A list of phases analyzed from the XRD spectra versus desired value ...... 70

Table 6-1 Tafel plot parameters ...... 89

List of Equations

Equation 2-1 ...... 2

Equation 2-2 ...... 3

Equation 2-3 ...... 5

Equation 2-4 ...... 5

Equation 2-5 ...... 6

Equation 2-6 ...... 6

Equation 2-7 ...... 14

Equation 2-8 ...... 14

Equation 2-9 ...... 16

Equation 2-10 ...... 21

Equation 2-11 ...... 21

Equation 2-12 ...... 21

Equation 3-1 ...... 34

Equation 4-1 ...... 44

Equation 4-2 ...... 44

Equation 4-3 ...... 57

Equation 4-4 ...... 61

Equation 5-1 ...... 68

Equation 6-1 ...... 83

Chapter 1. Introduction

1.1 Motivation

As world population grows, so does the energy demand. With the global temperature rising due to the Greenhouse effect at the same time, the search for clean, efficient, renewable energy source is of utmost importance[1]. Thermoelectric materials have been receiving attention due to their potential application in converting waste heat into electrical energy. Over the past fifty years, many laboratories worldwide have investigated room-temperature thermoelectric material with high efficiency. However, progress has been slow, as thermoelectric devices are still too inefficient to be cost- effective. Most thermoelectric alloys developed recently with high efficiency are toxic and have high production costs, making them unsuitable for everyday applications. The search continues for a naturally abundant, non-toxic material that can be easily modified to become thermoelectric generators.

Titanium dioxide (TiO2) is the naturally occurring oxide of titanium with interesting properties. It has many applications both in the industry and our everyday life, such as sunscreens and toothpaste, as pigments, photocatalysts or gas sensors[2]. A series of phases exist in the Ti-O system that has higher electrical conductivity than TiO2 called the Magnéli phases. These phases can be formed with simple reduction reaction, usually by carbon or hydrogen. Many have investigated and synthesized the Magnéli phase

TiO2, but the difference in production methods had yielded samples with different electrical and thermal characteristics[3-11]. Therefore, the objective of this research project would be to perform a comprehensive study on the electrical and thermal properties of the Magnéli phase and non-stochiometric TiO2 and the effect of oxygen defects on these properties.

1 Chapter 2. Literature Review

2.1 The Thermoelectric effect

The thermoelectric effect can be simply defined as the conversion of temperature difference into a voltage or vice versa[12]. It was first identified by Thomas J. Seeback in

1821 when he heated the junction between two conductors and creates an electromotive force. The combination of the two different conductors is referred to as a thermocouple.

The Seebeck effect can be explained as the raised temperature provide the electrons with enough energy to pass through the interface, hence generating a potential difference. The voltage produced is proportional to the difference in temperature between the two conductors. This proportionality constant is referred to as the Seebeck coefficient or thermopower. The Seebeck coefficient (α) can be expressed by the following expression:

Equation

2-1

Where V is the voltage obtained and is the change in temperature

Just thirteen years after, J. Peltier discovered the exact opposite. He noticed that if a current is passed through a thermocouple, it will heat up or cool down depending on the direction of the current. This temperature difference can be reasoned by the change in energy when electrons pass from one conductor to another.

In 1855, W. Thomson studied the Seebeck and Peltier effects and found that they are closely related and dependent on one another[13]. He also found that the thermoelectric effect can exist in a single homogenous conductor, in which the conductor generates a potential difference when there is a temperature gradient. This can be explained in terms of charge carriers, which carry charge as well as heat. Charge carriers tend to diffuse from the hot end to the cold end if a temperature gradient is introduced, thus creating a

2 potential difference[1]. This is the basis for electrical power generation by the thermoelectric effect.

2.1.1 Thermoelectric efficiency

To define the thermoelectric effect, several factors need to be taken into account. The thermoelectric effect by itself is reversible for there are no thermodynamic losses.[12].

However, both the heating by electrical resistance and thermal conduction phenomena that happened simultaneously are irreversible. Therefore, the efficiency of a thermoelectric material should be defined by the Seebeck coefficient, the thermal and electrical resistivities and the ratios of length to cross-sectional area. The figure of merit

(zT) is a dimensionless coefficient that defined this efficiency[14].

Equation 2-2

Where α is the Seebeck coefficient, T is the absolute temperature, ρ is the electrical resistivity, and κ is the thermal conductivity.

The efficiency of thermoelectric material is dependent on the material properties through the dimensionless figure of merit ZT. To maximize ZT, a large Seebeck coefficient, low electrical resistivity and low thermal conductivity are needed.

Nevertheless, many conflicts present themselves during the search for novel material.

Since the thermoelectric effect is based on the diffusion of charge carriers, carrier concentration would be an important parameter in consideration[1]. First of all, only one type of carrier should be present. Combined n-type and p-type carriers would cancel out the potential difference when they move in the same direction[15]. A low carrier

3 concentration would result in a large Seebeck coefficient, but also high electrical resistivity. This creates a dilemma, as these sets of parameters counter each other. A compromise needs to be made between a large Seebeck coefficient and a small electrical resistivity needs to be made if the efficiency is to be maximized. As shown in Figure 2-1, the optimal range would lie between 1019 and 1020 carriers per cm3, which indicates a heavily doped semiconductor.

[1] Figure 2-1 Maximizing figure of merit ZT through carrier concentration. Trends were modeled from Bi2Te3

The effective mass faces the same predicament, like that of carrier concentration; large effective mass yields large Seebeck coefficient, but lower carrier mobility[1]. Effective mass is closely related to carrier mobility. Materials composed of elements with small electronegativity differences usually have high carrier mobility and low effective mass[16]. Whereas polar ionic compounds are the exact opposite.

In summary, a thermoelectric material needs to be able to scatter phonon while leaving electrical conduction unhindered to achieve maximum efficiency[17]. Glass is a good example of a phonon scattering structure. Since their mean-free-path is only a few

4 interatomic spacing long, they have the lowest possible lattice thermal conductivities.

However, this also means high electrical resistivity caused by electron scattering and large effective mass. The desired material would have an electrical conductivity of crystals, as well as the thermal conductivity of glass.

2.1.2 Thermal conductivity

As mentioned in the previous section, a low thermal conductivity is required to achieve high thermoelectric efficiency. In a typical solid-state material, thermal conduction is a combination of two mechanisms; conduction by charge carriers( ), or phonons emitted by lattice vibration( )[1]. Total thermal conductivity can be expressed as follows:

Equation 2-3

Both hole (p-type) and free electron (n-type) carriers can partake in thermal conduction by carriers. In materials with large electrical conductivity, this would be the dominant conduction mechanism especially if the carrier concentration and mobility are at the optimum range. The Wiedemann-Franz law defines this as follows:

Equation 2-4

Where L is the Lorenz factor.

Assuming if κe dominate thermal conduction, substituting Equation 2-4 into the equation for ZT (Equation 2-2) would lead to the ZT only governed by the Seebeck coefficient. This means that the lattice thermal conductivity is very crucial when considering a good thermoelectric material since it is independent of the electronic structure[18].

The lattice thermal conductivity can be expressed as follows[18]:

Equation 2-5

Where vs is the speed of sound, Cv is the specific heat at constant volume, and l is the mean free path of the phonons.

At high temperatures, heat capacity is constant, meaning that will mostly be dependent on l, which is dependent on phonon to phonon scattering. Phonon mean free path can be reduced by either introducing point defects or lattice interfaces.

2.1.3 Seebeck coefficient

The Seebeck coefficient is the potential change as a function of change in temperature.

It is essential when describing the magnitude of charge induced by a temperature gradient. By the irreversible thermodynamics theory, the Seebeck coefficient is given as[19]:

Equation 2-6

Where is the Boltzmann constant, e is the electric charge, H is the heat transport, T is the absolute temperature, and is the chemical potential. Since H is relatively insignificant at high temperatures, S becomes dominated by the chemical potential. The chemical potential itself is defined by a combination of configurational entropy, the number of charge carriers and the internal energy and volume. Therefore, the Seebeck coefficient is very dependent on carrier concentration.

2.1.4 Ways to improve ZT

Recent discoveries of new mechanisms at a smaller length scale have sparked inspirations in the search for novel thermoelectric material. Narrowing of energy bands

6 caused by increasing quantum refinement will increase effective mass, and therefore larger Seebeck coefficients[1]. Also, electron filtering in engineered heterostructures may be able to separate the Seebeck coefficient from electrical conductivity.

As mentioned before, since heat transport by carriers is very closely related to electrical conductivity, to decrease it would be unwise. Therefore, the major direction now is to reduce the lattice thermal conductivity when designing materials. Many strategies had been developed to lower lattice thermal conductivity.

Disorder in the unit cell can certainly lead to low lattice thermal conductivity[20]. This can be done through interstitial sites, partial occupancies or rattling atoms as well as alloying[1]. Materials with large, cage-like crystal structures are especially useful. Since a crystal structure is needed for high electrical conductivity, atoms will form the skeleton of the structure and be responsible for conducting charge[21]. The large space in between the skeleton can then be filled with weakly bonded atoms or rattling atoms that scatter phonons[22]. This will yield a material with good electrical conductivity while the lattice thermal conductivity is reduced. Good examples of this are skutterudites and clathrates as shown in Figure 2-2.

Figure 2-2 Disorder in the unit cell. a.) skutterudites[21], b.) clathrates[23]

7 Complex unit cells can scatter phonons just as easily. In the case of Zn4Sb3, interstitial atoms induce lattice distortion which acts as scattering agents[23]. The interstitial Zn atoms act as the phonon glass, while the Sb skeleton provides electrical conductivity.

Another approach would be to design a material with specific sections responsible for different functions[1]. Metallic layers with higher electrical conductivity can be separated by insulating, disordered layers that scatter phonons. One example of this is cobaltite oxides (Figure 2-3a). Oxides usually have high thermal conductivity and low mobility, but the Co-O metallic layer in this case significantly increased mobility, while the disordered layers lower thermal conductivity. This indicated that oxide thermoelectric efficiency greatly depends on its structure.

[1] Figure 2-3 Separating the conduction routes . a.)NaxCoO2, b.) CaxYb1-xZn2Sb2

2.2 The Titanium-Oxygen system

Titanium oxides have many applications. They can be used in pigments, paints, photocatalytic and photovoltaic applications and sensors[24]. Modifications made to the material can result in different properties and as a result, different applications. Metal oxides usually have low mobility, but titanium oxide is known to have relatively higher electrical conductivity. This paper will discuss titanium oxides as a candidate for the commercialization of thermoelectric devices.

Titanium dioxide has good properties for thermoelectric applications such as a large

Seebeck coefficient and a relatively high electrical conductivity[25]. However, its high thermal conductivity lowers the overall efficiency, results in a ZT that is close to 0.003.

It has been reported that TiO2 with lower oxygen content not only has higher mobility but lower thermal conductivity as well[25, 26]. As such, reduced titanium dioxide will be the focus of this paper.

2.2.1 TiO2 Structures

[27] TiO2 has three different polymorphs; rutile, anatase, and brookite . Rutile is the most common naturally occurring form while anatase and brookite are relatively rare.

Structures of rutile and anatase are shown in Figure 2-4. They both have tetragonal unit cells, with one titanium atom surrounded by six oxygen atoms[28]. Rutile has smaller bond angles than anatase, resulting in longer Ti-Ti distances and larger density[29].

Figure 2-4. Bulk structures of rutile and anatase[2].

9 2.2.2 Reduced TiO2

In 1957, Magnéli et al.[30] studied a range of transition metal oxides with X-ray diffraction (XRD) and discovered a series of phases with the generic formula TinO2n-1, where n lies between four and ten. As shown in the phase diagram in

Figure 2-5, these phases exist in the range between TiO2 and Ti2O3, hence they can also

[31] be expressed as TiOx, where 1.66 < x < 2. This can then be divided into five regions .

1. 1.98 ≤ x < 2.00 (132) CSP appeared non-uniformly dispersed sparingly

[32] 2. 1.93 ≤ x ≤ 1.98 (132) CSP in orders of TinO2n-1, 16 ≤ n ≤ 36 3. 1.89 ≤ x ≤ 1.93 (132) CSP transform into (121) CSP 10 ≤ n ≤ 15

[32] 4. 1.75 ≤ x ≤ 1.89 (121) CSP in orders of TinO2n-1, 4 ≤ n ≤ 9

[31] 5. 1.66 ≤ x ≤ 1.75 Ti4O7 co-exist with Ti3O5

3+ 4+ The structure of Magnéli phase TiO2 has many types of defects such as Ti and Ti interstitials and crystallographic shear planes [2]. The dominant defect structure changes with the degree of oxygen deficiency. Despite Ti interstitials’ dominance in the region from TiO1.9996 to TiO1.9999, the crystallographic shear plane was reported as the

[33] main defect mechanism in Magnéli phase TiO2 .

Figure 2-5. Phase diagram of the Ti-O system[3]

As shown in Figure 2-6, TiO2 octahedra share corner and edge oxygens to connect with one another [26, 34, 35]. However, since an oxygen deficiency is introduced every nth layer

[36] in Magnéli phase TiO2, the octahedra share faces instead . This leads to a corundum layer at every nth layer, which can also be referred to as a crystallographic shear plane

(CSP). Overall, the structure of reduced TiO2 can be described as ordered layers with n

[14] layers of rutile followed by a layer of corundum (Ti2O3) . The diffusion mechanism involves the displacement of Ti ion planes to the next row, each ion moving through an

[37] octahedra face . The maximum number of CSP is reached at Ti4O7, for crystal reconstruction occurs when composition changes to Ti3O5 and then Ti2O3

[34] Figure 2-6 Different orientations of TiO2 octahedra

2.2.2.1 Electrical conductivity

The electrical conductivity of Magnéli phase TiO2 varies between different phases. As a conversion of Ti4+ to Ti3+ ion occurs every nth layer, we can expect the electrical conductivity to decrease as n increases[38]. This trend is demonstrated in Figure 2-7, with Ti2O3 and Ti3O5 being the exceptions. Since Magnéli phase TiO2 all go through semiconductor to metal transition at various temperatures, two conduction mechanism is considered[39, 40]. Under the transition temperature, Ti3+ ions covalently bond with one another as their 3d orbitals overlap[41, 42]. Consequently, the single 3d electron is occupied and thus unable to conduct charge in a metallic manner. Ti2O3 and Ti3O5 both have transition temperatures above room temperature, thus presents as outliers in Figure

2-7. Above the transition temperature, the metal-metal bonds break and Ti ion to Ti ion distance increases[43]. This leaves the 3d electrons free to partake in metallic conduction, resulting in significantly higher conductivity[44].

[43] Figure 2-7 Electrical conductivity of Magnéli phase TiO2

The actual conductivity of a reduced TiO2 sample is dependent on the particular Magnéli phase present and synthesis method[43]. A number of factors such as the density of the sample, presence of defects, grain size, and the presence of impurities associated with the synthesis method will have a significant impact on the resulting conductivity.

2.3 Synthesis method

Synthesis of Magnéli phase TiO2 can be done in several ways. Most of these methods

[45] adopt TiO2 as the titanium source for its easy availability and lower cost comparing to pure Ti metal. Reductants such as hydrogen, carbon and some active metals (e.g. Ti,

Mg or Ca) are added to remove oxygen[35]. The reaction usually requires high temperature and constant gas flow to displace oxygen emission. If oxygen fugacity in the reactor is controlled, even single crystals can be grown.

2.3.1 Carbothermic reduction

Reduction of TiO2 by carbon can be done in an inert atmosphere under high temperature, the expression is as below[35]:

13 Equation 2-7

For this reaction, the titanium to carbon ratio is crucial if the product phase is to be controlled. Works done by this method were listed in Table 2-1. From this, it can be summarized that while the ratio of carbon to TiO2 is important, the outcome phase is more dependent on the operating temperature[46].

The carbon sources to be consumed differ with various studies. Lu et al.[6] submerge titanium oxide plates in carbon power (diameter < 1.4mm), while Zhu et al.[47] chose carbon nano-powder instead. The two studies used the same reduction temperature, although Lu et al. use a slightly shorter holding time. However, Lu et al. obtained TiOx with a significantly larger x than that from Zhu et al. This could be the result of the difference between carbon particle size, as small particles implied increased surface area and increased contact to the bulk titanium dioxide.

2.3.2 Hydrogen reduction

Removal of oxygen by hydrogen reduction is the most common method of synthesizing

[35] Magnéli phase TiO2. The expression is as follows :

Equation 2-8

This process involves heating TiO2 to high temperatures (1073K to 1573K) in a hydrogen-rich environment. It is important to remove all traces of oxygen in this process, for reduced TiO2 oxidizes easily at moderately high temperatures.

Since the chemical and physical properties depend heavily on the specific phase

14 produced, analysis of monophasic samples would be required. However, despite careful

[48] control of all parameters, only monophasic Ti4O7 can be synthesized . This is caused by the different thermodynamic stability of the different phases. From Figure 2-8, it is apparent that only Ti4O7 has a wide window of stability that allows for monophasic reaction. As n increases, the equilibrium regions get narrower, and the difficulty to produce single-phase increases[49]. It also needs to be noted that the wide window of stability in Ti8O15 shown in Figure 2-8 is the result of the lack of data for n > 9 phases.

[48] Figure 2-8 Equilibrium phases for the hydrogen reduction of TiO2

Reported experimental procedures done to make reduced TiO2 by hydrogen reduction have been listed in Table 2-1. Parameters that are critical to the degree of reduction include the density of input material, the composition of gas feed, operating temperature and the time-scale of processing[45].

2.3.3 Metallothermic reduction

Reduction of TiO2 to Magnéli phase or non-stoichiometric titanium oxides can also be done with active metals such as Ca, Al, Na, Si, and Ti. Titanium, in particular, is ideal as monolithic phase can be produced by controlling the ratio of Ti and TiO2. The reaction

15 is as follows:

Equation 2-9

[30] The first study on Magnéli phase TiO2 was done by mixing titanium sponge and TiO2 under Ar gas. Similarly, arc melting at high temperatures was used to prepare Ti2O3.

[5] Another time, Gusev et al. prepared Magnéli phase TiO2 by mechanical activation. They mixed rutile and titanium powder and performed mechanical activation by grinding in a planetary mill. Then it was annealed under Ar atmosphere. Monolithic

Ti4O7 and Ti6O11 were obtained as a result.

16 Composition Structure Method Material Temperature Held time Pre-treatment Reference (°C) (hours)

n = 2-6 powder carbothermic PVA, N2 gas 700-1100 1 Different ratio of PVA/ TiO2 [50]

rutile fiber carbothermic Carbon 800-1100 12-24 Thermoplastic extrusion with stearic [51] powder, Ar acid as a pre-coating material, toluene gas as the solvent and polyethylene as the binder

n > 3 fibre carbothermic Carbon 1300 1 Same as above [51] powder, Ar gas

n = 4 disc hydrogen Pure H2 1050 4 5 wt% PEO solution added as a binder, [52] powder compacted in a uniaxial press and sintered for 1 day at 1050°C.

n = 3, 4 powder hydrogen 4% H2 in Ar 1180 2 Oxidation in O2 at 800°C for 2 hours, [53] reduced, then oxidized again

n = 6, 9 powder hydrogen 4% H2 in Ar 1000 2 Same as above [53]

n = 4-6 pellets hydrogen 10% H2 in Ar 1050 2 TiCl4 solution added with EDTA then [54] H2O2 to produce amorphous TiOx

powder 17 n = 22 pellets hydrogen 7% H2 in Ar, 1147 3.5 Powder pressed to form pellets, then [55] Anatase sintered at 1600K for 5 hours in air n = 100 pellets hydrogen 7% H2 in Ar, 997 3.5 Same as above [55] Anatase

Table 2-1 Reduction Parameters for various studies

17 2.4 Applications

Magnéli phase TiO2 has applications in many fields. These include chemical catalysts, environmental remediation, photovoltaics, fuel cells, and cathodic protection of steel in concrete.

Monolithic Ti4O7 had also been used in the cathodic protection of steel-reinforced bars in concrete[56]. Since the more commonly applied carbon or graphite would be slowly consumed via oxygen evolution, Ti4O7 was preferred for its higher corrosion resistance. Moreover, it is more stable than Ti under acidic conditions such as mud.

Environmental applications such as electrochemical decomposition of pollutants are also plausible. Due to Ti4O7’s high corrosion resistance, high electrical conductivity and strong adherence with the catalyst, it is highly effective as catalyst support in the electrochemical treatment of contaminants such as halogenated organic species or sulphites[45, 57]. Chen et al.[57]’s research indicated that the reduction of trichloroethylene

(TCE) and chloroform (CF) is first-order with Pt or Pd on Ti4O7 catalysts. Scott et al.[58] used Ti4O7 based electrodes to oxidize sulphur dioxide gas in a small scale sieve-plate electrochemical reactor. This treatment of SO2 is a cleaner and cheaper alternative to the consumption of chemical oxidants.

Titanium dioxide is well known for its intriguing photocatalytic properties. UV irradiation on the surface will initiate oxidation of toxic chemicals at relatively high efficiency at normal atmospheric conditions[53]. However, this only happens under UV,

[53] not visible light. Martyanov et al. reported that the reduction of TiO2 to Magnéli phase and subsequent re-oxidation would activate visible light oxidation. They also hypothesized that this activation of visible light could be caused by the oxygen defects

18 introduced in the reduction process.

19 2.5 Hydrogen Evolution Reaction

Hydrogen evolution reaction (HER) is the cathodic half of the electrochemical process of water electrolysis or water splitting, which is essentially the breaking down of water molecules into oxygen gas and hydrogen gas[59]. It allowed the production of ultra-high purity hydrogen gas. The HER takes place at the cathode while the oxygen evolution reaction (OER) occurs at the anode.

The HER enabled the production of hydrogen gas by electricity. Hydrogen gas is essential in many industrial processes including the formation of ammonia (NH3) by the Haber-Bosch process, and the production of industrial steel and aluminium=. Moreover, water electrolysis is one of the more efficient energy storage options and would be crucial in the commercialization of renewable energy. As of now, over 95% of hydrogen

[60] production is from the reformation of fossil fuels , which adds to CO2 emission. If the electricity generated from renewable technology can be used for water splitting, sustainable hydrogen can be produced, which in turn transforms some industrial processes to be sustainable. However, the cons for using this process is that it has relatively low efficiency, and good catalyst is often expensive noble metals.

HER efficiency is particularly dependent on the electrode material. The noble metals (Pt,

Rh and Ru) are among the best in the elements and Pt, in particular, is considered as the best one[61, 62]. However, their high cost prevented widespread commercialization.

Currently, mild steel and nickel are used as electrode materials for industrial hydrogen production. New and better electrode materials had been discovered, however, none has been implemented in large scale manufacture. Alloying had been known to increase the electrocatalytic activity of a material. The Brewer-Engel theory[63] predicts that when metals that have empty or half-empty d-orbitals are alloyed with metals that have

20 internally paired d-electrons, maximum bond strength and stability can be achieved[61].

However, the theory applies only to bulk properties, while the electrocatalytic performance relies more on surface chemistry and morphology.

2.5.1 Theory

HER involves the transformation of H+ ions to gaseous hydrogen. This usually takes place in a three-step process[62].

1. Equation 2-10

Where * is an active site on the catalyst surface and H* is a hydrogen atom adsorbed on the surface. This is known as the Volmer reaction, in which a hydrogen atom is adsorbed onto an active site. Then the protons transform into molecular H2 through either of the following:

Equation 2-11 2.

Equation 2-12 3.

These are the Heyrovsky and Tafel process respectively. Equation 2-11 represents the electrodissociation and combination of hydrogen, while Equation 2-12 showed the recombination of hydrogen atoms on the surface.

The kinetics of these reactions is dependent on many factors such as the nature of the electrolyte or the crystallinity of the electrode[64]. It is also known to change drastically if the pH of the electrolyte change from acidic to alkaline. Since the electrocatalytic performance is the best in acid medium, most studies are done with Pt as the electrode in acidic environment. There are two ways to enhance the performance of an electrode.

21 First is to increase the exchange current density, and the second is to increase the real surface area of the electrode[61]. In general, the performance of an electrode can be quantified by the Tafel parameters; that is the exchange current density (j0) and the slope

(b). For a good electrode, large j0 and small b are required. However, there are several problems when applying this quantification method[61]. The electrode real surface can only be estimated at best, but j0 is calculated as per geometric surface area. This makes it difficult to justify comparison studies. Moreover, complex reaction mechanisms and porous bulk structure will often induce non-linear Tafel plots. This means that the calculations for j0 would not be reliable.

2.5.2 Magnéli phase TiO2 as cathode for HER

Given the abundance of free charge carriers and the presence of free d-orbitals from the

3+ plane of Ti , the Magnéli phase TiO2 may be a promising cathode material for electrochemical reactions. They also have the advantage of being very corrosion resistant and stable in any pH[65]. Indeed, Magnéli phase materials have been studied as cathode material or conductive support in many electrochemical processes, such as lithium sulfur batteries[66, 67] and fuel cells[68, 69].

[70] Reduced TiO2 has great potential as catalyst supports in electrochemical applications . Catalyst supports are materials with high surface area and stability on which catalyst is attached on. Magnéli phase TiO2 can be used as a substitute for carbon supports due to its increased catalytic activity, higher stability, and corrosion resistance[70, 71]. In the case

[72] of Pt on Ti4O7 electrodes , while the electrochemical activity is similar to that of bulk

Pt, irreversible oxidation from Ti4O7 to Ti6O11 occurs. This passivates the surface that was not covered with catalyst, thereby prevented side reactions on supports. With enhanced catalyst stability, it is highly methanol tolerant of direct methanol fuel cells

22 (DMFC) and polymer electron membrane fuel cells (PEMFC) applications[73].

23 Chapter 3. Experimental Methods

3.1. Fabrication methods

3.1.1. Materials

Titanium (IV) oxide (99.9% trace metals basis) powder with a particle size of <5 um,

Polyvinyl alcohol () and Graphite (99.99% trace metal basis) were all purchased from

Sigma-Aldrich. Deionized water was used in all the procedures.

Rutile TiO2 was chosen since it is the most abundant form of titanium dioxide. Polyvinyl alcohol was dissolved in water to form 3 wt % solution before it is added to

TiO2 powder. The same materials were used throughout the entire thesis for consistency. High purity powder was chosen since the impurity may contribute to the reduction reaction, affecting the level of oxygen content in the process.

3.1.2. Hydrogen reduction

The hydrogen reduction method is the most commonly used for its effectiveness. The reaction is as follows:

The theory of this technology was explained in Section 2.3.2.

In a typical synthesis, the TiO2 powders were first pressed into pellets. The pellets were then loaded into a tube furnace and heated to 1100-1300°C at a heating rate of 5 K/min for 5-8 hours dwell time. Forming gas (Ar with 5% H2) was passed through the tube furnace at various flow rates. The pellet was then allowed to cool under the same conditions. They were then polished to remove the top layer in preparation to be characterized.

24 3.1.2.1. Pellet preparation

Three batches of pellets were made for the hydrogen reduction method.

To make the binder, 97 ml of water was heated up to 80°C. Then, 3 grams of polyvinyl alcohol powder was added, the solution was stirred until all solids dissolve to form 3 wt. % PVA solution.

In a typical batch of pellets, 15 grams of TiO2 powder were mixed with 6 drops of 3% PVA solution. They were then crushed with pestle and mortar for a few minutes until fine powder was obtained. Then, 6 more drops were added, the powder was to be crushed until no more agglomerates form. Only then the powder was ready to be pelletized.

They are press under the hydraulic press under various parameters listed in Table 3-1.

Table 3-1 Pressing parameters for the hydraulic press

Batch Die diameter Mass (g) Pressure Dwell (s) (mm) (kPa)

1 50 15 30 20

2 20 5 10 90

It should be noted that the pellets were shaped differently for each batch. Batch 1 was pressed with a 50mm diameter die and was cut into 8mm square pieces before being sintered. Batch 2, on the other hand, was pressed with a 20mm diameter die and was sintered without cutting.

25 3.1.2.2. Reduction parameters

The first batch was synthesized using the parameters listed in Table 3-2. A constant heating rate of 5 k/min was used.

Table 3-2 Reduction parameters for batch 1

Gas flow Sample Temperature Dwell time Mass (g) rate name (°C) (h) (mL/min)

0904 2.8 1200 5 100

0905 2.8 1200 5 200

0906 2.8 1300 5 200

1003 5 1300 8 100

1004 5 1100 8 100

1010 5 1300 5 200

1016 5 1200 5 200

1017 5 1200 8 200

1018 5 1300 8 200

Batch 2 was used to synthesize the samples listed in Table 3-3 for larger samples.

Table 3-3 Reduction parameters for batch 2

Temperature Gas flow rate Sample name Dwell time (h) (K) (mL/min)

0423 1573 5 100

0429 1473 5 100

0430 1573 5 200

0501 1473 5 200

0506 1573 8 200

0507 1473 8 200

0509 1473 8 100

0516 1573 8 100

3.1.3. Carbothermic reduction

Reduction by carbon was typically done by submerging the bulk samples in graphite (in flakes or Nanopowder form) and annealed under inert atmosphere and high temperature, usually between 1200 to 1300 °C. The expression is a follows:

In this thesis, carbothermic reduction was done to high-density TiO2 pellets sintered by the spark plasma sintering technique. The theory of this technology was explained in

Section 2.3.1.

27 3.1.3.1. Spark Plasma Sintering

Spark Plasma Sintering (SPS) was a novel process to acquire material with unique properties that were impossible for other processes. This technique was a combination of high temperatures generated by Joule heating, high axial press, low voltage and pulses of large direct current[74]. The large heating rate, as a result, managed to maintain nano-structures unaltered by minimizing microstructure growth. A schematic of a typical setup was demonstrated in

Figure 3-1.

Figure 3-1 Diagram of spark plasma sintering plant[74].

In this study, the SPS is mainly used to sinter and densify the brittle, crumbly samples.

28 Pre-reduced TiOx powder was loaded into a 20 mm graphite die and pre-pressed under

50 MPa. SPS was then done by the Dr. Sinter Spark Plasma Sintering Apparatus (SPS

Syntex Inc., Kawasaki, Japan). The samples were all sintered at 1273K for 5 minutes dwell under 50 MPa. The sample surfaces were lightly polished to remove graphite foil.

3.2. Characterization techniques

3.2.1. X-ray diffraction

X-ray Diffraction is a very widely used technique for characterizing crystalline and poly-crystalline materials. X-rays are electromagnetic radiation with just the right wavelength to be scattered by the electron clouds of an atom[75]. These diffracted waves sometimes interact with each other and produce stronger intensity peaks. In a crystal sample where atoms are arranged periodically, sharp interference peaks will be produced with respect to the distribution of atoms. This, in turn, allows us to analyze the distribution of atoms in a material.

Figure 3-2 Principles of X-ray Diffraction[76]

In this paper, this technique is prominently used to characterize the phase of the sample,

29 it allows us to define the samples base on their oxygen content. It should be noted that this method only analyzed the surface of the sample. The apparatus used in this paper are the PANalytical Xpert Multipurpose X-ray Diffraction System (MPD) and the

PANalytical Empyrean 2 Co Source XRD, in which the MPD used most of the times.

3.2.2. Optical microscopy

The optical microscopy (OM) and the scanning electron microscopy (SEM) are both imaging techniques that give magnified images of the sample surface. The OM uses a variety of lenses to refract visible light in order to achieve magnification. It is fast and adaptable, does not require sample preparation, and the images come out in real colours.

However, this method is limited to the sub-microns (~0.1 um), whereas the SEM can achieve a few nanometres.

Figure 3-3 A schematic drawing of an optical microscope[77]

30 3.2.3. Scanning Electron Microscopy

The Scanning Electron Microscopy (SEM) uses a focused electron beam to generate surface information. As the excited electrons hit the sample; secondary electrons, backscatter electrons, and characteristic X-rays are generated. These signals picked up by the detector are then processed by the computer to produce the image that we see on the computer screen. In a typical run, the sample is first mounted onto the specimen mount. If the sample is not conductive, it first needs to be sputter coated with gold with a thickness of 20 nm. The sample chamber is vacuumed to maintain a controlled environment with minimum contamination.

In this thesis, the aim of these imaging techniques was to see the surface morphology and to calculate the average pore size. The OM was first used to observe the pore size and finds that they are on average a few hundred microns, thus it was concluded that the

OM would be sufficient to calculate pore size. The SEM was then used to obtain a finer surface morphology.

3.2.4. Seebeck coefficient and electrical resistivity analysis

The Seebeck coefficient and electrical resistivity were both measured by the ULVAC-

RIKO ZEM-3 system. In this device, a rectangular sample is fixed between the top and the bottom electrodes, with two thermocouples connecting horizontally[78]. The sample needs to be cut or polished so that it is in perfect rectangular shape, in order for the top and bottom electrodes to make full contact with the sample. The sample chamber is then vacuumed to avoid contamination and heat interference. While the furnace heats up and holds the sample at a specific, constant temperature, the bottom electrode is heated up to a higher temperature to provide a temperature gradient. The Seebeck coefficient is calculated by first measuring the temperature difference, then the electromotive force

31 between the two thermocouples[78].

The electrical resistance measurement is done by the four-point probe method. This technique applies current from the top and bottom electrodes and measures voltage drop between the thermocouples by subtracting the thermos-electromotive force between the terminals.

Figure 3-4 Schematic of the ZEM-3 setup[78].

3.2.5. Thermogravimetric analysis

Thermogravimetric analysis is a technique to measure the change in mass of a material

(bulk or powder) when subjected to a change in temperature under controlled environment[79]. A typical setup consists of a precision balance in a temperature control furnace with purging gas that can be either inert or reactive. This method is widely used in thermal decomposition, phase transition, chemisorption, and solid-gas reactions analysis.

This technique is particularly useful in this paper, as it allows the quantification of the samples in turns of oxygen deficiency. When this technique is used on a sample with unknown oxygen deficiency TiO2-x, x can be calculated by measuring the mass of oxygen gained with the sample is re-oxidized at high temperature in air (20% O2, 80%

N2). From this data, we can compare the samples based on their oxygen content.

Figure 3-5 Schematic diagram of the thermogravimetric analysis system[80]

3.2.6. Thermal diffusivity analysis

Thermal conductivity ( ) is essential in the thermoelectric measurements. Since measuring it directly involves measuring heat fluxes which are hard to measure with accuracy, it is often calculated from other properties. Thermal conductivity is

33 determined by the combination of three factors: thermal diffusivity ( ), density ( ), and specific heat (Cp). The expression is as below:

Equation 3-1

In this thesis, thermal diffusivity was measured by a NETZSCH LFA-427 system. The sample was sprayed with graphite coating to ensure similar surfaces against the laser, then it is mounted into a sample holder in a furnace chamber. The chamber is then purged and vacuumed many times to avoid contamination. A pulsed laser is directed at the graphite coated side of the sample. The radiation sensor on the other side then measures the temperature change over time, allowing the computer to calculate thermal diffusivity[81].

Figure 3-6 Schematic of the LFA [82]

3.2.7. Differential scanning calorimeter analysis

The differential scanning calorimeter (DSC) technique was used to measure the specific heat of the samples. This method is very widely used as it determines melting, crystallization and glass transition temperatures. In this technique, the heat flow rate was first measured with an empty crucible and a reference standard to form the baseline.

Then it is measure again under the same temperature program with the sample, allowing the calculation of the specific heat.

For this study, sapphire was used as the reference, and three repeat measurements were taken for calibration. The device used in this study is the NETZSCH STA (499F1

Jupiter).

Figure 3-7 Schematic diagram of a DSC furnace[83]

3.2.8. Density measurements

Density measurements were done at room temperature by a gas pycnometer (AccuPyc II

1340 Pycnometer, Micromeritics). This technique works by measuring the pressure change as a result of the displacement of gas. First, the baseline was measured when an empty chamber was filled with a quantity of gas at known pressure. Then gas with the same quantity pressure was released into the sample chamber, and the pressure was measured. By the Ideal Gas Law, it is now possible to calculate the volume of the sample, with the pressure difference of the two-chamber and the volume of the empty chamber known.

Figure 3-8 Schematic of a pycnometer[84]

3.2.9. Carrier concentration and mobility measurements

Carrier concentration and mobility measurements were carried out by the AC field Hall effect (LakeShore 8404 HMS). The Hall effect describes how the charge carriers in a material move to one side when a magnetic field is applied to an electric current flowing through the material[85]. This causes a detectable potential difference that can be measured and with the combination of known parameters such as magnetic field, current and thickness, carrier concentration and carrier mobility can be calculated. It should be noted that the Hall effect is dependent on the type of charge carriers, as the

Hall voltage has a different polarity for positive and negative charge carriers. Therefore, it can be used on samples with mixed carriers.

3.2.10. UV-vis Spectroscopy

The Ultraviolet-visible spectroscopy is a useful technique to determine the band gap of a material. For electrons to partake in conduction, they require a specific minimum amount of energy to excite them and move to the conduction band, this energy is call the band gap energy[86]. Consequently, band gaps are larger for insulators and smaller

37 for semiconductors. For bulk samples, the diffuse reflection spectroscopy (DRS) is often used. In this technique, the reflection of light in the ultraviolet, visible and near- infrared regions are measured as a function of the wavelength.

The band gap measurements were done with the LAMBDA 950 UV/Vis

Spectrophotometers. The wavelength range is between 400 nm and 1600 nm with 4 nm intervals.

3.2.11. Linear Sweep Voltammetry

The Linear Sweep Voltammetry (LSV) is an electrochemical measurement technique in which the current at a working electrode is measured simultaneously as the potential between the working electrode and the reference electrode (RHE)[87, 88]. In this three- electrode system, a fixed potential range is often applied. The resultant curve would be dependent on three factors: the rate of the electron transfer reactions, the chemical reactivity of the material, and the potential scan rate[89].

The scan rate is the speed in which the potential is scanned, often expressed as voltage per second. At a slower scan rate, the diffusion layer would be able to grow much thicker. As a result, the flux on the electrode surface would be much lower[88]. Since the flux is proportional to the current, the current measured will be lower at slower scan rates[90]. Moreover, the rotation speed of the stirring mechanism is important as well.

Taking the example of a HER reaction, H+ ion is being adsorbed steadily near the electrode and the electrocatalyst. The rate in which more H+ are brought to the surface will consequently control the magnitude of current measured[91]. Additionally, the concentration of electrolytes will affect the measurement the same way the rotating stirring mechanism will.

The LSV measurements were done by Changyong Zhang from Professor David Waite’s group in the Water Research Centre of UNSW.

Figure 3-9 Schematic of typical LSV set-up

Chapter 4. Controlling the Oxygen Level of Magnéli Phase TiO2 with Hydrogen Reduction Technology

4.1. Introduction

The Magnéli phase TiO2 (TinO2n-1) presents a range of all n-type semi-conductors with high electrical conductivity. While these properties promise them to be good

39 thermoelectric materials, the mechanism of phonon-scattering oxygen vacancies is much more fascinating. The row of Ti3+ every nth layer often described as the sheer plane structure, in particular, is presumed to be the predominant mechanism for phonon- scattering. There are several methods to produce these Magnéli phases: Hydrogen reduction, carbon reduction, and metallic reduction.

Hydrogen reduction is one of the most popular methods to fabricate oxygen-reduced

Titanium oxide. In this method, pure hydrogen or forming gas (5% Hydrogen, 95%

Argon) was passed through a tube furnace while pelleted or powder TiO2 was being heated to high temperatures (mostly around 1473K). Studies had been done with this method, but none with all three parameters studied at the same time. Only a handful of these studies managed to produce single-phase Magnéli phase TiO2. Also, most studies focused on the lower Magnéli phases (4 ≤ n ≤ 7). As previously mentioned in Section

2.3.2, the thermodynamic stability of each phase decreases as n in TinO2n-1 increases. This steps up the level of difficulty to research the higher Magnéli phases as the window for a single-phase result grows impossibly small. On the other hand, if a variety of samples with mixed higher Magnéli phases can be fabricated, studies could be done to investigate how mixing the phases affect thermoelectric properties. Phase to phase interface may cause phonon scattering and therefore produces an unusually large lattice thermal conductivity.

The aim of this study is to investigate the effect of reduction parameters such as gas flow rate, temperature, and holding time on the reduction process and the final product.

This presents a better picture of the reduction process and in turn allows optimization of parameters in order to produce a specific phase, and will hopefully lead to the production of single-phase TiO2.

First, small pellets were used to give a rough estimate of how the parameters affect the reduction process. This is due to the wide range of parameters from existing literature that outputs drastically different results. A baseline needs to be established in order to test the range of parameters that would be used in the setup presented in this work.

4.2. Experimental procedure

Commercial TiO2 powder was mixed with binder (PVA) by pestle and mortar. The mixture was then pressed with an isostatic press under the condition listed in Table 3-1 for Batch 1. The 50mm in diameter pellet was then cut into 8mm squares for the reduction process. Reduction was carried out in a tube furnace, the reduction parameters were listed in Table 3-2. The pellets were left to cool naturally in the furnace, still under forming gas flow.

Exactly half a gram of each sample was then crushed with pestle and mortar in preparation for Thermogravimetric Analysis (TGA) to determine how much oxygen was reduced. The TGA involved heating a small amount (~80 mg) of powder sample under air (20% O2 and 80% N2) to up to 1273K. Finally, the remaining pellets were polished for the XRD analysis. Phase identification was verified by a typical Cu Ka X-ray diffraction system (Panalytica X/pert Pro MPD). A 2θ range of 10 to 70 degrees was chosen.

A second batch was pressed with the parameters listed in Table 3-1, for Batch 2. The pellets were sintered whole without damage, and two pellets were sintered during each run. The sintering parameters were listed in Table 3-3. The sample was left to cool

41 naturally while passing through the same flow rate of forming gas.

The surface of the pellets was lightly polished to remove the outside layer of TiO2 that oxidizes from the residual oxygen in the furnace. Exactly half a gram of the sample was

then removed and crushed with pestle and mortar in preparation for the TGA to

investigate the level of oxygen loss and the Differential Scanning Calorimetry (STA) to

measure the specific heat. The polished pellet first went through the XRD (Panalytica

X/pert Pro MPD) for phase identification, then it was cut with a diamond wheel cutter

into exactly 10mm square shape. The ULVAC-RIKO ZEM-3 system was used to

measure the Seebeck coefficient and electrical resistivity from 573K to1073K. The

thermal diffusivity was measured with the LFA-427, and Specific with NETZSCH STA

(499F1 Jupiter) in order to calculate thermal conductivities. Density measurements were

carried out by the AccuPyc II 1340 Pycnometer. The AC field Hall effect (LakeShore

8404 HMS) instrument was utilized to calculate Carrier concentration and mobility.

4.3. Results and discussion

4.3.1. Establishing the parameters

Figure 4-1 shows the TG diagram of the samples from Batch 1 when they were re-

(a) (b)

640 750 104 104 1200-200-8 1300-200-5 1200-200-5 1300-200-8 1200-100-5 1300-100-8 103 103 1200-200-5 1300-200-5 1100-150-8 Control Control

102 102

Mass (%) Mass Mass (%) Mass

101 101

100 100 200 400 600 800 42 200 400 600 800 o Temperature (oC) Temperature ( C) oxidized.

Figure 4-1 Weight changes in the oxygen loading annealing processes at a) 1200°C and b) 1300°C

There are two ways to confirm if the sample was completely oxidized and reverted back to 100% TiO2. First, when the mass stabilizes and ceases increasing as temperature increases further. Both Magnéli phase and non-stoichiometry TiO2 oxidizes quite readily, as demonstrated by the low initiation temperature for the oxidation reaction from Figure

4-1a. Since the oxygen partial pressure remains stable and relatively high, it could be assumed that the conditions were very much in favour of oxidation. Subsequently, it can be concluded that the reaction stopped because it was completely oxidized. Second, the colour change from black to white when it was oxidized. Oxygen deficient TiO2 has a very distinct charcoal black colour while lower Magnéli phases (4 ≤ n ≤ 7) are dark blue.

On the other hand, pristine TiO2 was brilliant white before being reduced. This implied that if the sample colour change back to white, it was completely oxidized.

In general, the oxidation reaction initiated at around 400 °C, whereas the reduction reaction initiated at around 1000 °C. This demonstrates that the oxidation reaction has lower activation energy than the reduction reaction. Moreover, it is immediately apparent that there are two distinct trend lines. The samples reduced at 1300°C have a higher termination temperature than the 1200°C samples, even if the end results have similar average oxygen deficiencies. This may be due to how lower Magnéli phases have higher termination temperature, and inadvertently pointed out that perhaps temperature is directly connected to phase.

Oxygen deficiency TiO2-x was calculated with the following equation reproduced from

43 ref [6]:

Equation

4-1

0 Where ∆W is the mass increase, W the original mass, and and are the molar weights of titanium dioxide and oxygen respectively. The reaction is as follows:

Equation

4-2

The calculated result is listed in Table 4-1. It is apparent that both temperature and flow rate have discernible influences on the reduction process. Dwell time, however, only shows improvement up to n = 5.

Table 4-1 Calculated oxygen deficiency for Batch 1

2-x n Temperature Flow rate Dwell time (h) (°C) (ml/min)

1.992 127.6 1200 100 5 (Control)

1.943 17.6 1100 100 8

1.903 10.3 1200 200 5

1.876 8.1 1200 100 5

1.861 7.2 1300 200 5

1.852 6.7 1200 200 5

1.849 6.6 1300 100 8

44 1.845 6.5 1200 200 8

1.815 5.4 1300 200 8

1.812 5.3 1300 200 5

The XRD spectra shown in Figure 4-2 confirmed the existence of the lower Magnéli phases (4 ≤ n ≤ 7) in the samples. However, the phases identified were not consistent with the TGA results. The sample represented by the black line only contains Ti8O15, but the TGA calculations output the n value to be 6.5. This is because the XRD spectra identify single phases but do not account for the higher Magnéli phases (n > 10) whereas the TGA results are averaged values.

45 ◊ Ti5O9 ● ■ Ti6O11 ● ♦ Ti7O13 ●

● Ti8O15 ◊ ● ■ 2 (control) ♦

1.845 ♦ ■ ■ ■ 1.849 ♦ ■ ■ ■ ♦ Intensity (a. u.) (a. Intensity 1.861 ♦ ■ ■ ■ 1.876 ◊ 1.815 ◊ ■ ◊ ◊ 1.812 ■

20 22 24 26 28 30 2q (o)

Figure 4-2 XRD spectra of samples from Batch 1

Table 4-2 A list of phases analyzed from the XRD spectra versus calculated value

2-x Primary Phase Secondary Phase Calculated n

1.845 8 - 6.5

1.849 6 7 6.6

1.861 6 7 7.2

1.876 6 - 8.1

1.815 5 6 5.4

1.812 5 6 5.3

The purpose of this experiment is to obtain the baseline and to get a general idea about the range of parameters that would be used specifically for this setup in order to start

46 producing bigger samples. It is critical to examine the cross-sections of the samples in order to ascertain the uniformity of the structure. It was hypothesized that the oxygen vacancies would diffuse from the surface into the structure and the release of oxygen molecules would create pores inside the bulk structure. Consequently, the pore size should reflect the level of oxygen deficiency. Figure 4-3 is the OM images of the cross- sections of each sample. It shows that the pore sizes remain relatively constant throughout, although they had shrunken a little bit right in the middle of the pellet.

Figure 4-3 also showed that as sample oxygen content decreases, the pore size increases, but concentration decreases. The average pore size is 4 μm in diameter for the 1.812 sample and 2 μm for the 1.943 sample.

(a) (b)

Figure 4-3 Optical Microscope images of samples from Batch 1 with different oxygen deficiencies (2-x).

a) 1.812, b) 1.852, c) 1.876, and d)1.943

47 Larger sized samples were required for thermoelectric properties testing. However, it

was hypothesized that larger samples would have lower oxygen content under the same

parameters due to reduced surface area. Therefore, the samples in Batch 2 were made

with similar parameters.

4.3.2. Phase identification

Figure 4-4 shows the weight change over temperature diagram of when Batch 2 was

700 780 102.5 102.5 1200-200-8 1300-200-5 1300-100-8 1200-100-5 102.0 1200-100-8 102.0 1300-200-8 1200-200-5 Control 1300-100-5

101.5 Control 101.5 Mass (%) Mass Mass (%) Mass 101.0 101.0

100.5 100.5

100.0 100.0 200 400 600 800 200 400 600 800 Temperature (oC) Temperature (oC)

oxidized, and Table 4-3 is the calculated

oxygen deficiency 2-x and n values.

Figure 4-4 Weight change during heating for samples from Batch 2

Table 4-3 Calculated oxygen deficiency for Batch 2 in ascending order

2-x n Temperature Flow rate Dwell time (h) (°C) (ml/min)

1.992 127.6 1200 100 5 (Control)

48 1.947 18.9 1200 100 5

1.924 13.2 1200 100 8

1.916 12 1200 200 8

1.912 11.3 1200 200 5

1.91 11.1 1300 100 5

1.906 10.6 1300 200 5

1.903 10.3 1300 100 8

1.892 9.3 1300 200 8

As expected, the samples made have much higher n values than those from Batch 1. The divergence into two distinct trend lines was still present, although at different temperatures. However, this directly contradicts the hypothesis from Batch 1, since the sample with the highest oxygen content has the same trend line as the one with the lowest. On the other hand, from Table 4-3 it is evident that temperature has the strongest influence on the n value, the role of flow rate and hold time are inconclusive. The surface area of the sample has a very significant impact on the oxygen state as evidenced by the drop from n = 8.1 to 18.9 under the same reduction condition. This may be due to the low oxygen diffusion rate inside the lattice that hinders further reduction. Presumably, the surface area may be an easier way to control oxygen deficiency under the same reduction condition.

Figure 4-5 presents the XRD spectra for the samples from Batch 2. First of all, it is apparent that a signature peak for each phase exists between 22o to 26o at an increment of approximately 0.5o, starting from n = 5, same as reported by Backhaus-Ricoult et al.[92] The peaks from 28o to 30o also show similar trends, however with smaller increments. Once the average n value reaches 12, the XRD spectra no longer complies

49 with the calculated TGA result. Since the spectra for n > 12 does not exist in the database utilized by this study and cannot be found in the literature, it could be hypothesized that the percentage ratio of these higher Magnéli phases would be a significant factor in their properties.

In addition, the average n values for Batch 2 were much higher than that of Batch 1, but the phases detected by the XRD remains in the same range. This is possibly because similar reduction conditions produce the same phases, but smaller surface area hinders diffusion and stops oxygen from getting out of the lattice, thus creating a surface with low n but cores with high n as evidenced by the OM image of the cross-section showed in

Figure 4-6.

50 ◊ Ti5O9 ○ Ti9O17

■ Ti6O11 □ Ti10O19 ♦ ♦ Ti7O13 ▲ Ti11O21 ■ □ ▲ ● Ti8O15 ○ ◊ ● 2 (control) ○ □ 1.924 ▲ ▲ ○ □ ♦ ♦ 1.916 ▲ ● ● ○ ■ 1.947

● ■

1.912 Intensity (a. u.) (a. Intensity ■ ◊ 1.910 ♦ ●

1.903 ■ ◊ ■ 1.906 ◊ ◊ 1.892

20 22 24 26 28 30 2q (o)

Figure 4-5 XRD spectra of Batch 2 samples

51 Table 4-4 A list of phases analyzed from the XRD spectra versus calculated value

2-x Primary Phase Secondary Phase Calculated n

1.947 9 10 18.9

1.924 10 11 13.2

1.916 10 11 12

1.912 8 - 11.3

1.91 7 8 11.1

1.906 6 5 10.6

1.903 6 - 10.3

1.892 5 - 9.3

In turns of morphology, the OM images in Figure 4-8 shows a similar trend to the Batch

1 samples. The samples with higher n have much more pores with small size, whereas the samples with lower n have fewer pores, but they are much bigger. This may be because the lower n samples were made with higher temperature, the diffusion rates were much higher, therefore oxygen diffuses out of the lattice more, resulting in fewer pores. Local diffusion was also more robust, thus creating bigger pores. On the other hand, Batch 2 samples, in general, have fewer pores than Batch 1 samples. This can be attributed to the longer diffusion path hindering the transformation from Ti4+ to Ti3+ and the release of oxygen. It puts pressure on the reduction process and therefore results in much higher n value, releasing less oxygen at the same time. This decreased discharge manifests as smaller pores.

As shown by

52 Figure 4-6, the pores were sections into three zones: small pores in the centre, large pores close to the surface, and medium pores at the surface. This is different from the results from Batch 1, where the pore size remains mostly constant throughout the cross- section. The longer diffusion path to the centre may be the reason behind this, as the slow diffusion rate only allows big pores to travel close to the surface before the reduction process terminates due to decreased temperature.

Figure 4-6 Cross-section of sample1.910 close to the surface.

4 μm

Figure 4-7 SEM image of the x = 1.910 sample

(a) (b)

Figure 4-8 Optical Microscope images of samples from Batch 2 with different oxygen deficiencies (2-x).

a) 1.896, b) 1.910, c) 1.916, and d) 1.947

Figure 4-7 is the SEM image of the genuine, freshly broken surface of a sample. This confirmed the presence of micro-pores with a diameter of 1 μm in average that is undetectable by the optical microscope. These pores would appear in large numbers in the higher Magnéli phases, particularly if the reduction temperature is low, due to the decreased diffusion rate.

54 4.3.3. Thermoelectric properties

Figure 4-9 is the plotted resistivity of the Batch 2 samples. As expected, samples with higher oxygen content tend to have higher resistivity. The trend is presented in Figure

4-10. The reduction process transforms Ti4+ into Ti3+, creating a crystallographic shear plane in the process. The Ti3+ plane has 3d orbital free electrons to partake in electrical conduction, thus giving it higher electrical conductivity. Subsequently, lower oxygen content will result in lower resistivity. Notably, the trend flattens out at x = 1.933. This may be due to the higher Magnéli phases transforming into free oxygen vacancies.

There had been attempts by this study to measure the electrical resistance of pristine

TiO2. However, the resistance of the pristine TiO2 was too high to be measured with the equipment in our lab. This is in accordance of the data observed in He et al.’s studies[25], which the electrical conductivity of the pristine TiO2 is between 0 - 0.05 104. This is several scales lower than that of the oxygen deficient TiO2 measured in this study. Such low conductivity further demonstrated how the material properties are drastically affected by the oxygen deficiency.

The sudden rise in resistivity from 450°C was unanticipated, however. Generally, resistivity decreases as temperature increases. This may be connected to the initiation temperature for the oxidation reaction observed in the TGA analysis from the previous section. Incomplete elimination of oxygen in the furnace will enable oxidation of the sample when the temperature rises above 400°C, and in turn, increase the resistivity of the sample. Here, this increase may cancel out the effect of temperature and overflow into an upward trend. It could also be said that the higher the oxygen content is, the tendency for reduction increases. This is significant as it hinted on the stability of the phase; the more oxygen there is, the more unstable it become. More studies with better

55 vacuuming conditions are required to confirm if this is the only reason for the increase.

1.8x10-4

1.892 1.6x10-4 1.903 1.906 1.910 1.4x10-4 1.912

m) 1.916

W W 1.924 1.2x10-4 1.947

1.0x10-4 Resistivity ( Resistivity

8.0x10-5

6.0x10-5

0 100 200 300 400 500 600 700 Temperature (oC)

Figure 4-9 The temperature dependence of resistivity for Batch 2

4.0x10-4

3.5x10-4

3.0x10-4

2.5x10-4 Resistivity [Ω∙m] Resistivity

2.0x10-4

1.5x10-4

1.89 1.90 1.91 1.92 1.93 1.94 1.95 2-x

Figure 4-10 Resistivity versus oxygen content at room temperature

56 1.892 100 1.903 1.906 2-x eV 80 1.910 1.912 1.892 1.124

2 1.916 1.903 1.09 60 1.924 1.906 1.149 1.947 1.91 1.022 (F(R)hv) 1.912 0.881 40 1.916 0.944 1.924 0.769 20 1.947 0.89

0 0.5 1.0 1.5 2.0 2.5 3.0 hv (eV)

Figure 4-11 Kubelka-Munk function versus energy plot for TiO2-x samples

Uv-vis spectra was done to measure band gaps for the TiO2-x samples. The calculations were done with the Kubelka-Munk Function and is given as follows[93]:

Equation 4-3

Where R is the diffuse reflectance, K and S are the absorption and scattering coefficients respectively.

The band gap of the pristine TiO2 is 3.05 eV [94] for its rutile phase. Figure 4-11 shows that the band gap increases as the oxygen content decreases. The average band gap for the TiO2-x samples is ~1 eV, which is much lower that that of the pristine TiO2.

Nevertheless, the small magnitude of the values more or less aligned with the values obtained from the electrical resistivity measurements.

57 The Seebeck coefficient is plotted in Figure 4-12. The Seebeck coefficient can be defined as the voltage produced under temperature change. Positive values indicated hole (p-type) conductor while negative value represents a carrier (n-type) conductor.

Since the signal obtained are all negative, it can be assumed that all Magnéli phases with n greater than five are all n-type conductors. This is to be expected as their main conduction mechanism is of free electrons from the Ti3+ planes. They follow a general trend like the electrical resistivity; as oxygen content increases, absolute Seebeck coefficient increases. Since the Seebeck coefficient is largely dependent on the carrier concentration and carrier mobility, measurements were done to assess the effect of oxygen deficiency on them.

The average Seebeck coefficient of the pristine TiO2 is around -6 x 10-4 V/K [25]. While the negative value clearly indicated a n-type conductor, this value was almost three times greater than that of the oxygen deficient TiO2 observed in this study. Despite the benefits of having a larger Seebeck coefficient, ultimately the low electrical conductivity has a larger impact on overall ZT.

Figure 4-13 is the plotted carrier concentration and mobility versus oxygen content for the Batch 2 samples. There is no distinguishable trend, but the value itself is noteworthy.

The average value of carrier concentration obtained in this study is 8 x 1026 m-3. This is much higher than that of Bi2Te3 shown in Section 2.1.3. In general, the carrier concentration and carrier mobility are interdependent. The higher carrier concentration usually results in a lower carrier mobility. The results obtained were similar to that of a material with high effective mass. The plots seem to follow a bell shape curve in general.

More studies would be required before definitive conclusions can be made.

-1.4x10-4 1.892 1.903 -1.6x10-4 1.906 1.910 1.912 -1.8x10-4 1.916 1.924 1.947 -2.0x10-4

-2.2x10-4 Seebeck Coefficient (V/K) Coefficient Seebeck -2.4x10-4

-2.6x10-4 0 100 200 300 400 500 600 700 Temperature (oC)

Figure 4-12 The temperature dependence of the Seebeck coefficient for Batch 2

(a) 2.0x1027

1.8x1027

1.6x1027

1.4x1027

1.2x1027

1.0x1027

8.0x1026

6.0x1026

Carrier concentration [1/m³] concentration Carrier 4.0x10

2.0x1026

0.0 1.89 1.90 1.91 1.92 1.93 1.94 1.95 2-x (b)

59 1.0x10-4

8.0x10-5

/ V.s) / 2 6.0x10-5

4.0x10-5

2.0x10-5 Carrier Mobility (m Mobility Carrier

0.0

1.89 1.90 1.91 1.92 1.93 1.94 1.95 2-x

Figure 4-13 a) carrier concentration and b) carrier mobility of the samples from Batch 2 versus oxygen deficiency

60 Thermal conductivities of the titanium oxide samples were calculated and plotted in

Figure 4-14. As mentioned in Section 2.1.2, thermal conductivity is divide into two parts: the charge carriers (κe) and lattice vibration (κl) according to the Wiedemann- Franz law. It means that thermal conduction can be separated into two distinct mechanisms: energy transfer through holes or electron diffusion, or through phonons produced by lattice vibration. The magnitude of the latter is largely dependent on the lattice’s ability to scatter phonons.

Thermal conduction by charge carrier can be given by:

Equation

4-4

Where L is the Lorenz number (L = 2.44 x 10-8), T is the absolute temperature, and is the electrical resistivity of the sample. The calculated carrier and lattice thermal conductivities were given in Figure 4-15.

First of all, it is apparent oxygen deficiency has very little effect on thermal conductivity.

Although there is an almost indistinguishable trend that when oxygen deficiency increases, the thermal conductivity decreases. The strong trend for carrier conduction was expected since the trend for electrical conductivity was well documented. However, the conduction part was too small (approximately 10% of total conductivity at most) to have an effect on the overall conductivity. This is surprising given the metallic conducting nature of these materials, it was hypothesized that carrier conduction would play a major role in thermal conduction. However, lattice thermal conduction is the dominant heat conduction mechanism here. Since it is mostly governed by phonon mean free path (l) at high temperatures, it could be said that lattice scattering by point defects and interfaces was not good enough for this materials. Nevertheless, their

61 [25] average thermal conductivity is still similar to that of TiO2 . Since TiO2-x has a much greater electrical conductivity, consequently greater carrier thermal conductivity, than

TiO2, the lattice component should also be smaller than that of TiO2. This means that lattice scattering by oxygen defects still have some effect, albeit a small one.

The general trend for thermal conductivity is to decrease until 400°C, then it increases and flattens out at 600°C. This can again be attributed to oxidation of the sample under standard vacuum condition since the oxidation initiation temperature is around 400°C.

Given how sensitive this material is to oxygen, future experiments would need either high vacuum or the addition of getters for more accurate results.

5.5 1.892 1.903 1.906 1.91 5.0 1.912 1.916 1.924 1.947

4.5

4.0 Thermal conductivity (W/mK) conductivity Thermal

3.5 300 400 500 600 700 Temperature (°C)

Figure 4-14 The temperature dependence of total thermal conductivity for Batch 2

62 (a)

0.45 1.892 1.903 0.40 1.906 1.91 1.912 0.35 1.916 1.924 0.30 1.947

0.25

0.20

0.15 Carrier thermal conductivity (W/mK) conductivity thermal Carrier

0.10 300 400 500 600 700 Temperature (°C)

(b)

5.2 1.892 5.0 1.903 1.906 4.8 1.91 1.912 1.916 4.6 1.924 1.947 4.4

4.2

4.0

3.8 Lattice thermal conductivity (W/mK) conductivity thermal Lattice 3.6

300 400 500 600 700 Temperature (°C)

Figure 4-15 The temperature dependence of a) Carrier thermal conductivity and b) Lattice thermal conductivity

63 The figure of merit ZT for the Batch 2 samples was shown in Figure 4-16. The underlying trend is that ZT increases with decreasing oxygen content, although it is not immediately apparent. The highest value obtained was ZT = 0.135 at 700°C when x =

1.906. Notably, the highest value does not come from the sample with the lowest oxygen content.

1.892 1.903 0.14 1.906 1.91 1.912 0.12 1.916 1.924 1.947 0.10

zT 0.08

0.06

0.04

0.02 300 400 500 600 700 Temperature (°C)

Figure 4-16 The temperature dependence of ZT

64 4.4. Summary

Oxygen-reduced TiO2-x samples were fabricated by the hydrogen reduction method, their phases were identified and thermoelectric performances were characterized.

Reduction temperature is the limiting factor in the reduction process since it sets boundaries on the phases obtained. While other parameters such as hold time and gas flow rate have a large influence as well, the temperature is still recommended to be the deciding variable for phase control in future experiments. The pore size is a surprisingly good indication of oxygen content if the green sample has the same size and shape, as samples with lower oxygen content have less, but larger pores. The samples are all n- type conductors, indicating that when n > 5, conduction by free electrons dominate electrical conduction. Both Seebeck coefficient and electrical conductivity increase when oxygen content decreases, due to the increasing number of charge carriers as more

Ti4+ transforms into Ti3+ forming crystallographic shear planes.

The thermoelectric performance was largely dependent on the high electrical conductivity and the high lattice thermal conductivity. Despite the high electrical conductivity, lattice conduction still dominated, giving a higher thermal conductivity in return. The highest ZT value is 0.135 at 700°C when x = 1.906. This value is in good agreement with previous studies.

65 Chapter 5. Controlling the Oxygen Level of Magnéli Phase TiO2 with Carbon Reduction Technology

5.1. Introduction

Carbothermic reduction can be done to fabricate oxygen-reduced TiO2. In this method, carbon flakes or nano-powder was used to extract oxygen out of the bulk structure. This can be done in two ways. First, submerging the green TiO2 pellet in graphite flakes and sinter under inert gas flow, and second, imbedding graphite flakes into the green pellet before reducing under inert gas flow.

The first method requires a large surface area, as reduction only takes place on the surface where carbon picks up oxygen. This process requires time and high temperature for high diffusion rates since the oxygen would need to diffuse out of the bulk structure to the surface. Contrary to reduction by hydrogen gas where contact with reductants is constant, this method requires constant pressure to press reductant against the sample surface. This is to guarantee complete and continual contact since solid reductant would be consumed and would create air pockets in the process.

The second method solved this problem by embedding the carbon flakes inside the green pellet. While oxygen still needs to diffuse out of the surface, there is more than enough contact inside the structure to ensure a sufficient reduction rate. However, this process contains two flaws. First, since the reaction consumes reductants, it will leave the structure with a lot more pores than those reduced by hydrogen gas. This will decrease bulk density and create a brittle and crumbly structure. Second, it is difficult to guarantee all embedded carbon will be consumed. From the previous chapter, it is confirmed that temperature plays a very important role in the reduction process, most of

66 this significance comes from its effect on diffusion rates. While controlling the amount of carbon embedded can certainly put a boundary on the phases produced, the amount of carbon consumed will depend again on the lattice diffusion rate. If some graphite had not been consumed, it will become a contaminant and affect later measurements. As a result, it is critical to do an XRD phase analysis for graphite identification before further measurements can be done.

In the end, the second method was chosen for this study. Spark plasma sintering (SPS) had been done after to further densify the samples as a solution to the low-density issue.

Higher reduction temperature and long holding time comparing to hydrogen reduction were applied since high diffusion rate was required to ensure 100% consumption.

5.2. Experimental procedure

Commercial TiO2 powder was mixed with **** graphite flakes by pestle and mortar. The mixture was then ball milled for one hour to ensure even distribution and grain size.

It was then pressed with a hydraulic press under the same condition for Batch 2 from the previous section listed in Table 3-1. This is to ensure maximum contact between

TiO2 and the reductant. The two pellets were then reduced in the same furnace under the same conditions: heating at 10K/min to 1300°C under a constant flow of Ar gas at 200 mL/min. The sample was then allowed to cool naturally, still under inert gas.

Desired phases can be obtained if the mass of encapsulated graphite is carefully calculated and controlled, under the assumption that all graphite was consumed by the reduction process. It can be obtained from the expression below:

Equation 5-1

Where n is the desired n value for TinO2n-1 and are the molar masses of graphite and TiO2 respectively. The target n value and percentage graphite are listed in Table 5-1.

Table 5-1 A list of target n value with % graphite and reduction parameters

Sample name Target n Percentage Temperature Holding time graphite (°C) (h) (wt %)

SPS-1 8 1.843 1300 8

SPS-2 5 2.917 1300 8

After reduction, the brittle sample was then crushed by pestle and mortar instead of a ball-mill. This is to avoid oxidation since high energy ball milling is known to excite and oxidize the material. Three grams of each power was then loaded into a graphite die pre-lined with graphite paper. It was pre-pressed under 50 MPa and sintered with the

SPS under the condition listed in Section. The process was done in vacuum to avoid oxidation under high temperature. The surfaces of the pellets were then lightly polished to remove graphite foil.

The polished pellet first went through the Co Ka X-ray diffraction system (PANalytical

Empyrean 2) instead of a typical Cu Ka XRD for higher intensities to determine the phases and to check for carbon contamination. Exactly half a gram of each sample was

68 then crushed with pestle and mortar in preparation for Thermogravimetric Analysis

(TGA) to determine how much oxygen was reduced. Then it was cut with a diamond wheel cutter into exactly 10mm square shape. The ULVAC-RIKO ZEM-3 system was used to measure the Seebeck coefficient and electrical resistivity from 573K to1073K.

The thermal diffusivity was measured with the LFA-427, and Specific with NETZSCH

STA (499F1 Jupiter) in order to calculate thermal conductivities. Density measurements were carried out by the AccuPyc II 1340 Pycnometer.

69 5.3. Results and discussion

5.3.1. Phase identification

Due to the possibility of un-consumed carbon contamination, it is necessary to analyze the samples by XRD before the TGA. If residual carbon remains, it will be lost during the oxidation process, thus creating a weight loss amidst the weight gain caused by the oxidation process. Consequently, the calculated n value will be much lower than the actual value. Figure 5-1 showed the XRD spectra of the carbon-embedded samples. The sample SPS-1 contains only the higher Magnéli phase samples, while SPS-2 contains the lower Magnéli phases. It is interesting how slightly different carbon content can produce results so drastically different. While SPS-2 mostly conforms to the desired product, SPS-1 is a few n’s higher.

Table 5-2 A list of phases analyzed from the XRD spectra versus desired value

Sample name Primary Phase Secondary Tertiary Phase Target n (n) Phase (n) (n)

SPS-1 10 11 - 8

SPS-2 5 4 6 5

The red dashed line is the signature peak for graphite at 27.49°. This confirmed the existence of residual graphite in the structure. Notably, there is more residual graphite in

SPS-1 than SPS-2. This explained why the phases obtain in SPS-1 is much higher than the desired value. Since the samples were confirmed to have carbon impurities, there is no need for a TGA analysis as it would be inaccurate with the mass loss of carbon oxidation.

70 C □ ▼ Ti O 4 7 □ ◊ Ti5O9

■ Ti6O11

□ Ti10O19

▲ Ti11O21 ◊ □ ▲

Intensity (a. u.) (a. Intensity SPS-1 ◊ ▼ ◊ ■

SPS-2

20 22 24 26 28 30 2q (o)

Figure 5-1 XRD spectra of SPS samples

Figure 4-3 shows the optical microscope images of cross-sections of the SPS samples.

The original was on the left, and the modified diagram with graphite highlighted in red was on the right. First of all, it seems that there are still a few pores even after spark plasma sintering. There could be a number of reasons for this, the first being small scale carbon reduction after sintering due to the presence of residual graphite. Even though high pressure prevented the formation of pores during the sintering process, cavities from the consumption of graphite may form during the cooling period where no pressure was exerted.

71 (a)

(b)

Figure 5-2 OM images of SPS samples a) SPS-1, b) SPS-2 graphite was highlighted in red.

72 5.3.2. Thermoelectric properties

[25] Data for the pure Ti4O7 phase was reproduced from a previous study to build a comparison of their thermoelectric properties with that of the SPS samples.

Figure 5-3 presents the electrical resistivity of the samples. SPS-2 has a very similar value to TiO1.77, most likely due to their similar oxygen content. They all seem to increase slightly after 500°C, although it is more pronounced in SPS-1. These values are in agreement with the values presented in Chapter 4. Due to the carbon contamination, it was expected to shift up since amorphous graphite has slightly larger resistivity than the samples from Chapter 4[95, 96]. However, the drift did not take place, and the results are in line with the reported values.

2.5x10-4 SPS-1 SPS-2

TiO1.77

2.0x10-4

m) W W 1.5x10-4

1.0x10-4 Resistivity ( Resistivity

5.0x10-5

0.0 0 100 200 300 400 500 600 700 Temperature (°C)

Figure 5-3 The temperature dependence of resistivity for SPS samples. Data for TiO1.77 was reproduced from ref [25]

73 SPS-1 -5.0x10-5 SPS-2 TiO1.77 -1.0x10-4

-1.5x10-4

-2.0x10-4

-2.5x10-4

-3.0x10-4 Seebeck coefficient (V/K) coefficient Seebeck

-3.5x10-4

-4.0x10-4 0 100 200 300 400 500 600 700 Temperature (°C)

Figure 5-4 The temperature dependence of the Seebeck coefficient for SPS samples. Data for TiO1.77 was reproduced from ref [25]

The Seebeck coefficient of the SPS samples was plotted in Figure 5-4. The values are all negative, indicating a free electron (n-type) conductor. This result is again mostly in agreement with the trend discovered in Chapter 4. However, the Seebeck coefficient for the SPS samples seems to decrease at an increased rate compared to samples from

Chapter 4, although the reported value of TiO1.77 did not follow this trend. This could be due to the graphite contamination in the SPS samples. It could be hypothesized that while graphite has equal numbers of both types of charge carriers at room temperature[97], the number of free electrons will increase as temperature increases. This will lead to an increase in both magnitude and decreasing rate for the Seebeck coefficient. On the other hand, if it is indeed the result of carbon pollution, SPS-1 should have a higher decreasing rate than SPS-2 because SPS-1 has a higher carbon content.

74 4.0

3.9 SPS-1 SPS-2 3.8 TiO1.77

3.7

3.6

3.5

3.4 Thermal conductivity (W/mK) conductivity Thermal 3.3

3.2 300 400 500 600 700 Temperature (°C)

Figure 5-5 The temperature dependence of thermal conductivity for SPS samples. Data for TiO1.77 was reproduced from ref [25]

Thermal conductivities of the SPS samples were calculated and plotted in Figure 5-5.

Thermal conductivity, by definition, is a combination of thermal diffusivity, density, and specific heat. The carrier and lattice thermal conductivities were derived from the

Wiedemann-Franz Law, in which thermal conductivity is separated into two types.

It is immediately apparent that the values for SPS samples have drastically different trends than the reported values. Since the specific heat values for the reported values are unknown, it is possible that is where the discrepancy originated from. The specific heat values for the SPS samples are under different trends comparing to the values obtained in Chapter 4. A possible explanation may lie again in carbon pollution. Residual graphite fragments may hinder thermal conduction by acting as scattering points for

75 phonons, thereby decreasing lattice thermal conductivity. This could also be the cause of the lower value. On another note, even though the reported value did not follow the general shape from Chapter 4, the values are aligned. This affirmed the existence of the trend which is previously unclear. The lower value for SPS-1 comparing to SPS-2 could be due to strong phonon scattering from interfaces between multiple phases. However, since there are supposed to be more CSPs in SPS-2, it could be hypothesized that the interfaces between phases in higher Magnéli phases are more effective at scattering phonons than that at lower phases. Also, there are more pores in SPS-1 than SPS-2, the increased number of air pockets will decrease its thermal conductivity. Moreover, because SPS samples were sintered after reduction, there might be an increased number of interface and boundaries that would induce phonon scattering, thereby lowering thermal conductivity. However, the thermal conductivities of graphite is much higher than that of TiO2, but the thermal conductivity had not increased. This hinted that the effect of the interfaces, grain boundaries and the pores outweighs the effect of the impurity itself.

Furthermore, the downward trend of the thermal conductivities for SPS samples is in itself unusual. Typically, thermal conductivity increases at higher temperatures due to increasing lattice vibration and higher carrier energy. Since thermal conductivity by charge carriers does not show such a trend, conduction by lattice vibration must be the reason for this downward trend.

It was hypothesized that the bulk density of the SPS samples will be much higher than the samples from Chapter 4 since the latter only went through the hydraulic press and did not go through another round of pressing after reduction. However, the results are contrary to this hypothesis. The densities of the samples have very similar values. This

76 could be again caused by the graphite impurities in the structure, as graphite have much lower bulk density than titanium oxide. This weakening of the bulk structure may cause several problems including reduced corrosion resistance that will lead to partial corrosion. Since carbon is known to degrade at high pH, this limited its application in fuel cell technologies.

77 (a)

1.2 SPS-1 1.1 SPS-2

1.0 TiO1.77 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2

Carrier thermal conductivity (W/mK) conductivity thermal Carrier 0.1 0.0 100 200 300 400 500 600 700 Temperature (°C)

(b)

3.6 SPS-1 3.5 SPS-2 3.4 TiO1.77 3.3 3.2 3.1 3.0 2.9 2.8 2.7 2.6

Lattice thermal conductivity (W/mK) conductivity thermal Lattice 2.5 2.4 300 400 500 600 700 B

Figure 5-6 The temperature dependence of a) Carrier thermal conductivity and b) lattice thermal conductivity for

SPS samples. Data for TiO1.77 was reproduced from ref [25]

78 The calculated ZT versus temperature was plotted in Figure 5-7. The SPS samples have slightly higher ZT values than the reported sample. On the other hand, the values observed in Chapter 4 are much lower than this. This could be caused by a number of reasons. First, the thermal conductivity of the SPS samples is much lower, which is caused by increased phonon scattering from improved sintering techniques and carbon impurities. Second, the electrical conductivities and Seebeck coefficient are all generally higher than the samples from Chapter 4 even though they seem to follow the same trend. This is due to the extra charge carriers introduced by graphite at higher temperatures.

0.30

SPS-1 0.25 SPS-2

TiO1.77

0.20

ZT 0.15

0.10

0.05

300 400 500 600 700 Temperature (°C)

Figure 5-7 The temperature dependence of ZT for SPS samples. Data for TiO1.77 was reproduced from ref [25]

5.4. Summary

Carbon-reduced titanium sub-oxide samples were successfully synthesized. This method has the advantage of higher affordability, safety, and stability. However, the presence of residual graphite impurities poses as a serious complication if high purity products were required. Despite this, the carbon impurities actually improved the thermoelectric properties of the samples. Graphite contamination brings a number of benefits. Increased Ti-C interfaces scatter phonons which in turn decreases lattice thermal conductivity. Moreover, extra free electron charge carrier is introduced at high temperatures, thereby increasing both the electrical conductivity and the Seebeck coefficient. The combination of these factors results in much higher ZT values. Despite these advantages, graphite contaminations ultimately weakened the bulk structure and decrease the density even after SPS.

The highest value obtained for ZT was ZT = 0.27 at 700°C for the SPS-2 sample. This not only is decidedly higher than the samples from Chapter 4, but also higher than the

TiO1.77 data extracted from He et al.’s study[25]. It could be hypothesized that the lowest Magnéli phase (Ti4O7) is not the

80 Chapter 6. Magnéli Phase TiO2 as Cathode Material in

HER

6.1. Introduction

Sustainable technologies had been the research focus for the past decade or so.

Hydrogen evolution reaction (HER) is among one of the most studied electrochemical systems for its ability to produce high purity hydrogen gas. If the electricity generated from renewable energy sources was used for this process, this would be the most sustainable practice for hydrogen production. It can also act as a form of energy storage, for hydrogen gas is fuel by itself. However, water splitting only produces less than 4% of the total hydrogen production. This is due to the low efficiency and high cost if good electrocatalysts were to be implemented.

The Magnéli phase TiO2 has a number of properties that prove to be advantageous if it’s used as cathode electrode for hydrogen evolution reaction. It has a high electrical conductivity that enabled efficient electron transfer to the surface, large real surface area from the abundant pores on the surface and good chemical stability. While it’s a very poor catalyst for the oxygen evolution reaction for its high OR potential, it is stable enough to be electrode material for water splitting[43]. It has been well documented that the performance of Magnéli phase TiO2 electrodes is much more dependent on the pore size distribution on the surface of the electrode [43, 52, 73].

Most of the studies that had been done on Ti4O7 because they have the highest electrical conductivity among the Magnéli phases. In some cases, they had been used as electrocatalysts supports because of their strong metal-support interaction (SMSI) and high conductivity dispersion[73]. The latter enhances catalytic activity since Ti3+ may

81 behave as hypo d-component that interacts with metallic d-phase. While they have the ability to replace carbon supports for they don’t decompose at high pH, they generally require much larger overpotential than Pt-C electrodes[43].

In this study, the samples made in Chapter 4 had been selected to study their electrocatalytic performance. Due to the abundance of pores in the structure that indicated a large specific surface area, good performance is expected.

6.2. Experimental Procedure

Samples from Chapter 4 with different oxygen content was selected. The phase was characterized by the TGA as well as the XRD.

The electrochemical characterization was performed by linear sweep voltammetry

(LSV). Platinum wire was used as the counter electrode. The reference electrode was

Ag/AgCl, and the electrolyte was 0.5 M H2SO4 at room temperature. The sweep range was 0 V to -5 V, with 1 mV intervals. Measurements were done in different scanning speeds: 2 mV/s, 10 mV/s, and 50 mV/s, with a CHI660E electrochemical workstation.

The LSV measurements were done by Changyong Zhang from Professor David Waite’s group in the Water Research Centre of UNSW.

82 6.3. Results and Discussion

6.3.1. Polarization curves

Polarization curves for the Magnéli phase TiO2 samples were plotted in Figure 6-1, Figure 6-2 and Figure 6-3 under a scan rate of 2 mV/s, 10 mV/s and 50 mV/s respectively.

The potential was converted relative to the reference electrode with the following equation:

o E(RHE) = EAg/AgCl + 0.059 pH + E Ag/AgCl Equation 6-1

o Where E(RHE) is the potential (V vs RHE), EAg/AgCl is the working potential, and E Ag/AgCl

o [98, 99] is the potential of the Ag/AgCl electrode (E Ag/AgCl = 0.197 with saturated solution ).

Since pH is close to zero in 0.5 M H2SO4, E(RHE) = EAg/AgCl + 0.197. Mass-transport overpotentials were not corrected since the electrolyte is in liquid form. iR ohmic drop

[100, 101] corrections were done for 0.5 M H2SO4 solution.

It is immediately apparent that the polarization curves extrapolated are not at all in good order. Generally, polarization curves for HER start from zero current and remain so until the potential reaches the onset potential, from which current experiences a sharp decrease. However, most of the curves for Magnéli phase TiO2 samples encountered a small slope at the beginning of the measurement. This makes it really difficult to determine the active region to be plotted with the Tafel plot, and consequently determine the onset potential for HER.

Moreover, the magnitude of measured current differs drastically across different scan rates. The magnitude drop for current as scan speed decreases was expected since the

83 thicker diffusion layer will influence the surface flux which in turn is proportional to current.

Most importantly, it is apparent that the current induced is not zero when the applied voltage is zero. This could be caused by a number of reasons. First, the current density is converted from current and effective surface area. This means that the curvature would be very dependent on the accuracy of surface area measurements. Moreover,

It is interesting that the curves for all TiO1.910 samples are remarkably different from all other curves. This may be attributed to their real surface area being different, although the OM images say otherwise. It could be possible that some of the large pores on the surface for the higher Magnéli phase samples are actually connected to the pores inside the structure, leading to a significantly larger surface area. However, the curve of the

TiO1.892 sample has a similar trend to the higher Magnéli phase samples. More studies need to be done for concrete rationale to be made.

Moreover, it seems that oxygen content has very little effect on the onset overpotentials of the samples. The onset overpotential is defined as the potential in which a redox half- reaction is observed. The onset overpotentials observed for the samples are very similar, but the induced current density is different. Overall, TiO1.892 and TiO1.916 have the lowest activity among the samples. This could be indicative of their lower real surface area.

84 0.10

0.05

) 2 0.00

j (mA / cm / (mA j -0.05 1.892 1.906 1.910 -0.10 1.916 1.947

-0.15 -0.3 -0.2 -0.1 0.0 0.1 0.2 Potential (V vs RHE)

Figure 6-1 Polarization curve for Magnéli phase TiO2 samples scanned at 2 mV/sec

0.10

0.05

0.00

-0.05

) 2 -0.10

-0.15

j (mA / cm / (mA j -0.20 1.892 -0.25 1.906 1.910 -0.30 1.916 1.947 -0.35

-0.40 -0.30 -0.25 -0.20 -0.15 -0.10 -0.05 0.00 0.05 0.10 Potential (V vs RHE)

Figure 6-2 Polarization curve for Magnéli phase TiO2 samples scanned at 10 mV/sec

85 0.4

0.2

0.0 )

-2 -0.2

-0.4 j (mA cm (mA j -0.6 1.892 -0.8 1.906 1.910 -1.0 1.916 1.947 -1.2 -0.3 -0.2 -0.1 0.0 0.1 Potential (V vs RHE)

Figure 6-3 Polarization curve for Magnéli phase TiO2 samples scanned at 50 mV/sec

86 6.3.2. Tafel plots

The Tafel slopes for the Magnéli phase TiO2 samples are plotted in Figure 6-5 and

Figure 6-4. The Tafel parameters are listed in Table 6-1. The slope for TiO1.910 cannot be calculated as the onset potential cannot be determined.

Overall, TiO1.916 has the largest Tafel slope while TiO1.892 has the smallest slope. The small slope represents a fast increase in the hydrogen generation rate[102]. This could be due to TiO1.892 having the highest electrical conductivity. Moreover, TiO1.892 also has the lowest onset overpotential, making it the sample with the highest overall performance. Despite this, the relationship between oxygen content and electrochemical performance is still known.

The exchange current density (j0) is calculated by extrapolating the parameters from the

Tafel plot. Being another good indication for performance, j0 is the current observed at zero potential. It’s an indication of the rate of electron transfer between the sample and the electrode. Among the samples, TiO1.916 has the highest exchange current density of 3.47 x 10-2 mV/cm2.

It is interesting how the plots differ just because the scan rate is different regardless of the magnitude difference. The onset overpotentials scanned with faster scanning speeds have significantly lower onset potential. This is possibly due to the thickening of the diffusion layer on the surface as scan speed decreases. Moreover, the ranking order of both the onset potential and the Tafel slope changes at different scanning speeds. A possible reason could be that the thickening diffusion layer has more effect on some sample than the other.

0.45 1.892 0.40 1.906 1.916 -1 0.35 1.947 252 mV dec

0.30

0.25

292 mV dec-1 495 mV dec-1 Overpotential (V) Overpotential 0.20

-1 0.15 149 mV dec

0.10 -2.0 -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 log ( j ) (mA cm-2)

Figure 6-4 Tafel slopes for Magnéli phase TiO2 samples scanned at 10 mV/sec

0.5 1.892 1.906 0.4 1.916 1.947 252 mV dec-1 0.3 -1 183 mV dec 320 mV dec-1

0.2 Overpotential (V) Overpotential

-1 0.1 235mV dec

0.0 -1.5 -1.0 -0.5 0.0 log ( j ) (mA cm-2)

Figure 6-5 Tafel slopes for Magnéli phase TiO2 samples scanned at 50 mV/sec

Table 6-1 Tafel plot parameters

10 mV/s 50 mV/s

2-x Slope Exchange Overpotenti Slope Exchange Overpotent current al current ial (mV/dec) (mV/dec) density density (mV) (mV) (mA cm-2) (mA cm-2)

1.892 149 2.31 x 10-3 145 235 2.46 x 10-2 120

1.906 292 4.72 x 10-3 246 252 1.53 x 10-2 187

1.916 495 3.45 x 10-2 259 320 3.47 x 10-2 249

1.947 252 2.74 x 10-3 278 183 3.61 x 10-3 184

89 6.4. Summary

The electrochemical performance of the Magnéli phase TiO2 samples had been analyzed for the hydrogen evolution reaction. Even though the polarization curves went through iR correction, the resultant curve still does not follow the typical patterns. This may be caused by inaccurate measurement of the surface areas of the samples. While the high conductivities did increase the performance, it is ultimately not the dominant mechanism that determines performance. The results seem to agree with the theory that the performance of the Magnéli phase TiO2 samples are more dependent on the surface structure than the electronic properties. Measurements scanned at different scanning rates have a dramatically different outcome.

Among the five samples, TiO1.892 has the highest performance with an onset overpotential of 145 mV and a Tafel slope of 149 mV/dec while TiO1.910 has the lowest performance. It is still not clear what happened to the TiO1.910 sample for its curves to be so drastically different than the others.

90 Chapter 7. Conclusion and Future Works

This study fabricated Magnéli phase TiO2 with various oxygen content. Their thermoelectric performances had been analyzed and the factors affecting both the reduction outcome and their thermoelectric properties had been examined.

The reduction of TiO2 by hydrogen is very dependent on the reduction temperature. The reduction process was done in a tube furnace while passing through forming gas (5%

H2). Reduction parameters including temperature, gas flow rate and holding time are recorded. The lower Magnéli phases (n = 5 and 6) will only be produced at higher temperatures (1573K) regardless of other reduction parameters. However, the phase distribution and total oxygen content will still change with gas flow rate and holding time.

The thermoelectric efficiency is very much dependent on the oxygen content. The samples are all n-type conductors, indicating that when n > 5, conduction by free electrons dominate electrical conduction. Both electrical conductivity and Seebeck coefficient increase when oxygen content decreases, while thermal conductivity remains mostly unchanged. The combination of these factors means that as oxygen content decreases, their thermoelectric performance increases. Even though high electrical conductivity would mean higher carrier thermal conductivity, lattice vibration dominated thermal conduction in this material. The highest ZT value was ZT = 0.135 at

700°C when x = 1.906.

Carbon reduction to fabricate Magnéli phase TiO2 has also been explored. A fixed weight percentage of Graphite powder was mixed with TiO2 powder and subsequently reduced in a tube furnace under inert gas after being pressed. It was then crushed and

91 then sintered with SPS to further densify the sample. From XRD analysis, the presence of residual graphite is confirmed. This impurity provides a number of benefits, especially in thermoelectric performance. It increases the electrical conductivities and

Seebeck coefficient by introducing extra charge carriers at high temperature, while also decreasing thermal conductivity by introducing point defects and interfaces. However, it also weakens the material by decreasing both density and resistance to corrosion. The highest value obtained for ZT was ZT = 0.27 at 700°C for the SPS-2 sample.

The electrochemical performance of the Magnéli phase TiO2 samples had been analyzed for the hydrogen evolution reaction. The oxygen content had very little effect on the electrochemical performance of the samples. It was possible that the real surface area has more effect than the oxygen content, although high electrical conductivity can still be advantageous. Among them, TiO1.892 has the highest performance with an onset overpotential of 145 mV and a Tafel slope of 149 mV/dec while TiO1.910 has the lowest performance.

In conclusion, the dependence of the thermoelectric performance of the Magnéli phase

TiO2 on their oxygen content was studied. The results indicated that oxygen content has a strong influence on the thermoelectric properties. Decreasing oxygen content would increase the thermoelectric performance if n < 5. On the other hand, the carbon reduced sample with graphite impurities had much higher ZT values despite similar oxygen content. This was mainly because the contamination introduces point defects and complex interfaces that act as phonon scattering sites, thereby greatly decreasing the lattice thermal conductivity.

To further investigate the reduction techniques and the effect of oxygen content on

92 thermoelectric properties, more studies need to be done:

 Rietveld refinement of nonstoichiometric TiO1.892-1.947 for more detailed phase data

 Fabrication and characterizations of Magnéli phase TiO2 by carbon reduction

without residual graphite.

 Fabrication and characterizations of single-phase Ti4O7

 Fabrication and characterizations of Magnéli phase TiO2 by mixing higher and

lower phases

 Photocatalytic properties of nonstoichiometric TiO1.892-1.947

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