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- All Subjects: Materials Science
- Creators: Alford, Terry L.
Description
Microwave (MW), thermal, and ultraviolet (UV) annealing were used to explore the response of Ag structures on a Ge-Se chalcogenide glass (ChG) thin film as flexible radiation sensors, and Te-Ti chalcogenide thin films as a material for diffusion barriers in microelectronics devices and processing of metallized Cu. Flexible resistive radiation sensors consisting of Ag electrodes on a Ge20Se80 ChG thin film and polyethylene naphthalate substrate were exposed to UV radiation. The sensors were mounted on PVC tubes of varying radii to induce bending strains and annealed under ambient conditions up to 150 oC. Initial sensor resistance was measured to be ~1012 Ω; after exposure to UV radiation, the resistance was ~104 Ω. Bending strain and low temperature annealing had no significant effect on the resistance of the sensors. Samples of Cu on Te-Ti thin films were annealed in vacuum for up to 30 minutes and were stable up to 500 oC as revealed using Rutherford backscattering spectrometry (RBS) and four-point-probe analysis. X-ray diffractometry (XRD) indicates Cu grain growth up to 500 oC and phase instability of the Te-Ti barrier at 600 oC. MW processing was performed in a 2.45-GHz microwave cavity on Cu/Te-Ti films for up to 30 seconds to induce oxide growth. Using a calibrated pyrometer above the sample, the temperature of the MW process was measured to be below a maximum of 186 oC. Four-point-probe analysis shows an increase in resistance with an increase in MW time. XRD indicates growth of CuO on the sample surface. RBS suggests oxidation throughout the Te-Ti film. Additional samples were exposed to 907 J/cm2 UV radiation in order to ensure other possible electromagnetically induced mechanisms were not active. There were no changes observed using XRD, RBS or four point probing.
ContributorsRoos, Benjamin, 1990- (Author) / Alford, Terry L. (Thesis advisor) / Theodore, David (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research emphasizes the use of low energy and low temperature post processing to improve the performance and lifetime of thin films and thin film transistors, by applying the fundamentals of interaction of materials with conductive heating and electromagnetic radiation. Single frequency microwave anneal is used to rapidly recrystallize the damage induced during ion implantation in Si substrates. Volumetric heating of the sample in the presence of the microwave field facilitates quick absorption of radiation to promote recrystallization at the amorphous-crystalline interface, apart from electrical activation of the dopants due to relocation to the substitutional sites. Structural and electrical characterization confirm recrystallization of heavily implanted Si within 40 seconds anneal time with minimum dopant diffusion compared to rapid thermal annealed samples. The use of microwave anneal to improve performance of multilayer thin film devices, e.g. thin film transistors (TFTs) requires extensive study of interaction of individual layers with electromagnetic radiation. This issue has been addressed by developing detail understanding of thin films and interfaces in TFTs by studying reliability and failure mechanisms upon extensive stress test. Electrical and ambient stresses such as illumination, thermal, and mechanical stresses are inflicted on the mixed oxide based thin film transistors, which are explored due to high mobilities of the mixed oxide (indium zinc oxide, indium gallium zinc oxide) channel layer material. Semiconductor parameter analyzer is employed to extract transfer characteristics, useful to derive mobility, subthreshold, and threshold voltage parameters of the transistors. Low temperature post processing anneals compatible with polymer substrates are performed in several ambients (oxygen, forming gas and vacuum) at 150 °C as a preliminary step. The analysis of the results pre and post low temperature anneals using device physics fundamentals assists in categorizing defects leading to failure/degradation as: oxygen vacancies, thermally activated defects within the bandgap, channel-dielectric interface defects, and acceptor-like or donor-like trap states. Microwave anneal has been confirmed to enhance the quality of thin films, however future work entails extending the use of electromagnetic radiation in controlled ambient to facilitate quick post fabrication anneal to improve the functionality and lifetime of these low temperature fabricated TFTs.
ContributorsVemuri, Rajitha (Author) / Alford, Terry L. (Thesis advisor) / Theodore, N David (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Zinc oxide (ZnO) has attracted much interest during last decades as a functional material. Furthermore, ZnO is a potential material for transparent conducting oxide material competing with indium tin oxide (ITO), graphene, and carbon nanotube film. It has been known as a conductive material when doped with elements such as indium, gallium and aluminum. The solubility of those dopant elements in ZnO is still debatable; but, it is necessary to find alternative conducting materials when their form is film or nanostructure for display devices. This is a consequence of the ever increasing price of indium. In addition, a new generation solar cell (nanostructured or hybrid photovoltaics) requires compatible materials which are capable of free standing on substrates without seed or buffer layers and have the ability introduce electrons or holes pathway without blocking towards electrodes. The nanostructures for solar cells using inorganic materials such as silicon (Si), titanium oxide (TiO2), and ZnO have been an interesting topic for research in solar cell community in order to overcome the limitation of efficiency for organic solar cells. This dissertation is a study of the rational solution-based synthesis of 1-dimentional ZnO nanomaterial and its solar cell applications. These results have implications in cost effective and uniform nanomanufacturing for the next generation solar cells application by controlling growth condition and by doping transition metal element in solution.
ContributorsChoi, Hyung Woo (Author) / Alford, Terry L. (Thesis advisor) / Krause, Stephen (Committee member) / Theodore, N. David (Committee member) / Arizona State University (Publisher)
Created2012
Description
HgCdTe is currently the dominant material for infrared sensing and imaging, and is usually grown on lattice-matched bulk CdZnTe (CZT) substrates. There have been significant recent efforts to identify alternative substrates to CZT as well as alternative detector materials to HgCdTe. In this dissertation research, a wide range of transmission electron microscopy (TEM) imaging and analytical techniques was used in the characterization of epitaxial HgCdTe and related materials and substrates for third generation IR detectors. ZnTe layers grown on Si substrates are considered to be promising candidates for lattice-matched, large-area, and low-cost composite substrates for deposition of II-VI and III-V compound semiconductors with lattice constants near 6.1 Å. After optimizing MBE growth conditions including substrate pretreatment prior to film growth, as well as nucleation and growth temperatures, thick ZnTe/Si films with high crystallinity, low defect density, and excellent surface morphology were achieved. Changes in the Zn/Te flux ratio used during growth were also investigated. Small-probe microanalysis confirmed that a small amount of As was present at the ZnTe/Si interface. A microstructural study of HgCdTe/CdTe/GaAs (211)B and CdTe/GaAs (211)B heterostructures grown using MBE was carried out. High quality MBE-grown CdTe on GaAs(211)B substrates was demonstrated to be a viable composite substrate platform for HgCdTe growth. In addition, analysis of interfacial misfit dislocations and residual strain showed that the CdTe/GaAs interface was fully relaxed. In the case of HgCdTe/CdTe/ GaAs(211)B, thin HgTe buffer layers between HgCdTe and CdTe were also investigated for improving the HgCdTe crystal quality. A set of ZnTe layers epitaxially grown on GaSb(211)B substrates using MBE was studied using high resolution X-ray diffraction (HRXRD) measurements and TEM characterization in order to investigate conditions for defect-free growth. HRXRD results gave critical thickness estimates between 350 nm and 375 nm, in good agreement with theoretical predictions. Moreover, TEM results confirmed that ZnTe layers with thicknesses of 350 nm had highly coherent interfaces and very low dislocation densities, unlike samples with the thicker ZnTe layers.
ContributorsKim, Jae Jin (Author) / Smith, David J. (Thesis advisor) / McCartney, Martha R. (Committee member) / Alford, Terry L. (Committee member) / Crozier, Peter A. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Estimation of complex permittivity of arsenic-doped silicon is the primary topic of discussion in this thesis presentation. The frequency that is of interest is 2.45 GHz, frequency typically used in conventional microwave ovens. The analysis is based on closed-form analytical expressions of cylindrical symmetry. A coaxial/radial line junction with the central conductor sheathed in dielectric material, which is As-doped silicon in this case, are analyzed. Electrical and magnetic field equations governing the wave propagation in this setup are formulated by applying the necessary boundary conditions. Input admittance is computed using the fields in the device and reflection coefficient is calculated at the input. This analytical solution is matched to the reflection coefficient acquired by experiments conducted, using VNA as the input source. The contemplation is backed by simulation using High Frequency Structural Simulator, HFSS. Susceptor-assisted microwave heating has been shown to be a faster and easier method of annealing arsenic-doped silicon samples. In that study, it was noticed that the microwave power absorbed by the sample can directly be linked to the heat power required for the annealing process. It probes the validity of the statement that for arsenic-doped silicon the heating curve depends only on its sheet properties and not on the bulk as such and the results presented here gives more insight to it as to why this assumption is true. The results obtained here can be accepted as accurate since it is known that this material is highly conductive and electromagnetic waves do not penetrate in to the material beyond a certain depth, which is given by the skin depth of the material. Hall measurements and four-point-probe measurements are performed on the material in support of the above contemplation.
ContributorsVaradan, Siddharth Kulasekhar (Author) / Alford, Terry L. (Thesis advisor) / Pan, George W (Thesis advisor) / Myhajlenko, Stefan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Damage detection in heterogeneous material systems is a complex problem and requires an in-depth understanding of the material characteristics and response under varying load and environmental conditions. A significant amount of research has been conducted in this field to enhance the fidelity of damage assessment methodologies, using a wide range of sensors and detection techniques, for both metallic materials and composites. However, detecting damage at the microscale is not possible with commercially available sensors. A probable way to approach this problem is through accurate and efficient multiscale modeling techniques, which are capable of tracking damage initiation at the microscale and propagation across the length scales. The output from these models will provide an improved understanding of damage initiation; the knowledge can be used in conjunction with information from physical sensors to improve the size of detectable damage. In this research, effort has been dedicated to develop multiscale modeling approaches and associated damage criteria for the estimation of damage evolution across the relevant length scales. Important issues such as length and time scales, anisotropy and variability in material properties at the microscale, and response under mechanical and thermal loading are addressed. Two different material systems have been studied: metallic material and a novel stress-sensitive epoxy polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
ContributorsZhang, Jinjun (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Semiconductor manufacturing economics necessitate the development of innovative device measurement techniques for quick assessment of products. Several novel electrical measurement techniques will be proposed for screening silicon device parameters. The studied parameters range from oxide reliability, and carrier lifetime in MOS capacitors to the power MOSFET reverse recovery.
It will be shown that positive charge trapping is a dominant process when thick oxides are stressed through the ramped voltage test (RVT). Exploiting the physics behind positive charge generation/trapping at high electric fields, a fast I-V measurement technique is proposed that can be used to effectively distinguish the ultra-thick oxides' intrinsic quality at low electric fields.
Next, two novel techniques will be presented for studying the carrier lifetime in MOS Capacitor devices. It will be shown that the deep-level transient spectroscopy (DLTS) can be applied to MOS test structures as a swift mean for screening the generation lifetime. Recombination lifetime will also be addressed by introducing the optically-excited MOS technique as a promising tool.
The last part of this work is devoted to the reverse recovery behavior of the body diode of power MOSFETs. The correct interpretation of the LDMOS reverse recovery is challenging and requires special attention. A simple approach will be presented to extract meaningful lifetime values from the reverse recovery of LDMOS body-diodes exploiting their gate voltage and the magnitude of the reverse bias.
It will be shown that positive charge trapping is a dominant process when thick oxides are stressed through the ramped voltage test (RVT). Exploiting the physics behind positive charge generation/trapping at high electric fields, a fast I-V measurement technique is proposed that can be used to effectively distinguish the ultra-thick oxides' intrinsic quality at low electric fields.
Next, two novel techniques will be presented for studying the carrier lifetime in MOS Capacitor devices. It will be shown that the deep-level transient spectroscopy (DLTS) can be applied to MOS test structures as a swift mean for screening the generation lifetime. Recombination lifetime will also be addressed by introducing the optically-excited MOS technique as a promising tool.
The last part of this work is devoted to the reverse recovery behavior of the body diode of power MOSFETs. The correct interpretation of the LDMOS reverse recovery is challenging and requires special attention. A simple approach will be presented to extract meaningful lifetime values from the reverse recovery of LDMOS body-diodes exploiting their gate voltage and the magnitude of the reverse bias.
ContributorsElhami Khorasani, Arash (Author) / Alford, Terry L. (Thesis advisor) / Goryll, Michael (Committee member) / Theodore, David (Committee member) / Arizona State University (Publisher)
Created2015
Description
The healthcare system in this country is currently unacceptable. New technologies may contribute to reducing cost and improving outcomes. Early diagnosis and treatment represents the least risky option for addressing this issue. Such a technology needs to be inexpensive, highly sensitive, highly specific, and amenable to adoption in a clinic. This thesis explores an immunodiagnostic technology based on highly scalable, non-natural sequence peptide microarrays designed to profile the humoral immune response and address the healthcare problem. The primary aim of this thesis is to explore the ability of these arrays to map continuous (linear) epitopes. I discovered that using a technique termed subsequence analysis where epitopes could be decisively mapped to an eliciting protein with high success rate. This led to the discovery of novel linear epitopes from Plasmodium falciparum (Malaria) and Treponema palladium (Syphilis), as well as validation of previously discovered epitopes in Dengue and monoclonal antibodies. Next, I developed and tested a classification scheme based on Support Vector Machines for development of a Dengue Fever diagnostic, achieving higher sensitivity and specificity than current FDA approved techniques. The software underlying this method is available for download under the BSD license. Following this, I developed a kinetic model for immunosignatures and tested it against existing data driven by previously unexplained phenomena. This model provides a framework and informs ways to optimize the platform for maximum stability and efficiency. I also explored the role of sequence composition in explaining an immunosignature binding profile, determining a strong role for charged residues that seems to have some predictive ability for disease. Finally, I developed a database, software and indexing strategy based on Apache Lucene for searching motif patterns (regular expressions) in large biological databases. These projects as a whole have advanced knowledge of how to approach high throughput immunodiagnostics and provide an example of how technology can be fused with biology in order to affect scientific and health outcomes.
ContributorsRicher, Joshua Amos (Author) / Johnston, Stephen A. (Thesis advisor) / Woodbury, Neal (Committee member) / Stafford, Phillip (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014
Description
Peptide microarrays have been used in molecular biology to profile immune responses and develop diagnostic tools. When the microarrays are printed with random peptide sequences, they can be used to identify antigen antibody binding patterns or immunosignatures. In this thesis, an advanced signal processing method is proposed to estimate epitope antigen subsequences as well as identify mimotope antigen subsequences that mimic the structure of epitopes from random-sequence peptide microarrays. The method first maps peptide sequences to linear expansions of highly-localized one-dimensional (1-D) time-varying signals and uses a time-frequency processing technique to detect recurring patterns in subsequences. This technique is matched to the aforementioned mapping scheme, and it allows for an inherent analysis on how substitutions in the subsequences can affect antibody binding strength. The performance of the proposed method is demonstrated by estimating epitopes and identifying potential mimotopes for eight monoclonal antibody samples.
The proposed mapping is generalized to express information on a protein's sequence location, structure and function onto a highly localized three-dimensional (3-D) Gaussian waveform. In particular, as analysis of protein homology has shown that incorporating different kinds of information into an alignment process can yield more robust alignment results, a pairwise protein structure alignment method is proposed based on a joint similarity measure of multiple mapped protein attributes. The 3-D mapping allocates protein properties into distinct regions in the time-frequency plane in order to simplify the alignment process by including all relevant information into a single, highly customizable waveform. Simulations demonstrate the improved performance of the joint alignment approach to infer relationships between proteins, and they provide information on mutations that cause changes to both the sequence and structure of a protein.
In addition to the biology-based signal processing methods, a statistical method is considered that uses a physics-based model to improve processing performance. In particular, an externally developed physics-based model for sea clutter is examined when detecting a low radar cross-section target in heavy sea clutter. This novel model includes a process that generates random dynamic sea clutter based on the governing physics of water gravity and capillary waves and a finite-difference time-domain electromagnetics simulation process based on Maxwell's equations propagating the radar signal. A subspace clutter suppression detector is applied to remove dominant clutter eigenmodes, and its improved performance over matched filtering is demonstrated using simulations.
The proposed mapping is generalized to express information on a protein's sequence location, structure and function onto a highly localized three-dimensional (3-D) Gaussian waveform. In particular, as analysis of protein homology has shown that incorporating different kinds of information into an alignment process can yield more robust alignment results, a pairwise protein structure alignment method is proposed based on a joint similarity measure of multiple mapped protein attributes. The 3-D mapping allocates protein properties into distinct regions in the time-frequency plane in order to simplify the alignment process by including all relevant information into a single, highly customizable waveform. Simulations demonstrate the improved performance of the joint alignment approach to infer relationships between proteins, and they provide information on mutations that cause changes to both the sequence and structure of a protein.
In addition to the biology-based signal processing methods, a statistical method is considered that uses a physics-based model to improve processing performance. In particular, an externally developed physics-based model for sea clutter is examined when detecting a low radar cross-section target in heavy sea clutter. This novel model includes a process that generates random dynamic sea clutter based on the governing physics of water gravity and capillary waves and a finite-difference time-domain electromagnetics simulation process based on Maxwell's equations propagating the radar signal. A subspace clutter suppression detector is applied to remove dominant clutter eigenmodes, and its improved performance over matched filtering is demonstrated using simulations.
ContributorsO'Donnell, Brian (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Bliss, Daniel (Committee member) / Johnston, Stephen A. (Committee member) / Kovvali, Narayan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Transparent conductive oxides (TCO) comprise a class of materials that exhibit unique combination of high transparency in the visible region along with high electrical conductivity. TCOs play an important role as transparent electrodes for optoelectronic devices such as solar cell panels, liquid crystal displays, transparent heat mirrors and organic light emitting devices (OLED). The most commonly used transparent electrodes in optoelectronic applications is indium tin oxide (ITO) due to its low resistivity (~ 10−4 Ω-cm) and high transmittance (~ 80 %). However, the limited supply of indium and the growing demand for ITO make the resulting fabrication costs prohibitive for future industry. Thus, cost factors have promoted the search for inexpensive materials with good electric-optical properties.
The object of this work is to study the structure-property-processing relationship and optimize a suitable transparent electrode with the intent to optimize them for flexible optoelectronics applications. The work focuses on improved processing of the mixed oxide (indium gallium zinc oxide, IGZO) thin films for superior optical and electrical properties. The study focuses on two different methods of post-deposition annealing-microwave and conventional. The microwave annealing was seen to have the dual advantage of reduced time and lower temperature, as compared to conventional annealing. Another work focuses on an indium free transparent composite electrode (TCE) where a very thin metal layer is inserted between the two TCO layers. A novel Nb2O5/Ag/Nb2O5 multilayered structure can exhibit better electrical and optical properties than a single layered TCO thin film. The focus for low cost alternative leads to a TiO2/metal/TiO2 based TCE. A systematic study was done to understand the effect of metal thickness and substituting different metals (Ag, Cu or Au) on the opto-electrical properties of the TCEs. The TiO2/Ag/TiO2 with mid Ag thickness 9.5 nm has been optimized to have a sheet resistance of 5.7 Ohm/sq. average optical transmittance of 90 % at 550 nm and figure of merit with 61.4 ×10-3 Ω-1. The TCEs showed improved optical and electrical properties when annealed in forming gas and vacuum. These dielectric/metal/dielectric multilayer TCEs have lower total thickness and are more efficient than a single-layer ITO film.
The object of this work is to study the structure-property-processing relationship and optimize a suitable transparent electrode with the intent to optimize them for flexible optoelectronics applications. The work focuses on improved processing of the mixed oxide (indium gallium zinc oxide, IGZO) thin films for superior optical and electrical properties. The study focuses on two different methods of post-deposition annealing-microwave and conventional. The microwave annealing was seen to have the dual advantage of reduced time and lower temperature, as compared to conventional annealing. Another work focuses on an indium free transparent composite electrode (TCE) where a very thin metal layer is inserted between the two TCO layers. A novel Nb2O5/Ag/Nb2O5 multilayered structure can exhibit better electrical and optical properties than a single layered TCO thin film. The focus for low cost alternative leads to a TiO2/metal/TiO2 based TCE. A systematic study was done to understand the effect of metal thickness and substituting different metals (Ag, Cu or Au) on the opto-electrical properties of the TCEs. The TiO2/Ag/TiO2 with mid Ag thickness 9.5 nm has been optimized to have a sheet resistance of 5.7 Ohm/sq. average optical transmittance of 90 % at 550 nm and figure of merit with 61.4 ×10-3 Ω-1. The TCEs showed improved optical and electrical properties when annealed in forming gas and vacuum. These dielectric/metal/dielectric multilayer TCEs have lower total thickness and are more efficient than a single-layer ITO film.
ContributorsDhar, Aritra (Author) / Alford, Terry L. (Thesis advisor) / Petuskey, William (Thesis advisor) / Krause, Stephen (Committee member) / Chizmeshya, Andrew (Committee member) / Arizona State University (Publisher)
Created2015