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Layer structured two dimensional (2D) semiconductors have gained much interest due to their intriguing optical and electronic properties induced by the unique van der Waals bonding between layers. The extraordinary success for graphene and transition metal dichalcogenides (TMDCs) has triggered a constant search for novel 2D semiconductors beyond them. Gallium

Layer structured two dimensional (2D) semiconductors have gained much interest due to their intriguing optical and electronic properties induced by the unique van der Waals bonding between layers. The extraordinary success for graphene and transition metal dichalcogenides (TMDCs) has triggered a constant search for novel 2D semiconductors beyond them. Gallium chalcogenides, belonging to the group III-VI compounds, are a new class of 2D semiconductors that carry a variety of interesting properties including wide spectrum coverage of their bandgaps and thus are promising candidates for next generation electronic and optoelectronic devices. Pushing these materials toward applications requires more controllable synthesis methods and facile routes for engineering their properties on demand.

In this dissertation, vapor phase transport is used to synthesize layer structured gallium chalcogenide nanomaterials with highly controlled structure, morphology and properties, with particular emphasis on GaSe, GaTe and GaSeTe alloys. Multiple routes are used to manipulate the physical properties of these materials including strain engineering, defect engineering and phase engineering. First, 2D GaSe with controlled morphologies is synthesized on Si(111) substrates and the bandgap is significantly reduced from 2 eV to 1.7 eV due to lateral tensile strain. By applying vertical compressive strain using a diamond anvil cell, the band gap can be further reduced to 1.4 eV. Next, pseudo-1D GaTe nanomaterials with a monoclinic structure are synthesized on various substrates. The product exhibits highly anisotropic atomic structure and properties characterized by high-resolution transmission electron microscopy and angle resolved Raman and photoluminescence (PL) spectroscopy. Multiple sharp PL emissions below the bandgap are found due to defects localized at the edges and grain boundaries. Finally, layer structured GaSe1-xTex alloys across the full composition range are synthesized on GaAs(111) substrates. Results show that GaAs(111) substrate plays an essential role in stabilizing the metastable single-phase alloys within the miscibility gaps. A hexagonal to monoclinic phase crossover is observed as the Te content increases. The phase crossover features coexistence of both phases and isotropic to anisotropic structural transition.

Overall, this work provides insights into the controlled synthesis of gallium chalcogenides and opens up new opportunities towards optoelectronic applications that require tunable material properties.
ContributorsCai, Hui, Ph.D (Author) / Tongay, Sefaattin (Thesis advisor) / Dwyer, Christian (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Collective cell migration in the 3D fibrous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. A migrating cell also generates active pulling forces, which are transmitted to the ECM fibers via focal adhesion complexes. Such active forces consistently

Collective cell migration in the 3D fibrous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. A migrating cell also generates active pulling forces, which are transmitted to the ECM fibers via focal adhesion complexes. Such active forces consistently remodel the local ECM (e.g., by re-orienting the collagen fibers, forming fiber bundles and increasing the local stiffness of ECM), leading to a dynamically evolving force network in the system that in turn regulates the collective migration of cells.

In this work, this novel mechanotaxis mechanism is investigated, i.e., the role of the ECM mediated active cellular force propagation in coordinating collective cell migration via computational modeling and simulations. The work mainly includes two components: (i) microstructure and micromechanics modeling of cellularized ECM (collagen) networks and (ii) modeling collective cell migration and self-organization in 3D ECM. For ECM modeling, a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization is devised. Analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. For modeling collective migratory behaviors of the cells, a minimal active-particle-on-network (APN) model is developed, in which reveals a dynamic transition in the system as the particle number density ρ increases beyond a critical value ρc, from an absorbing state in which the particles segregate into small isolated stationary clusters, to a dynamic state in which the majority of the particles join in a single large cluster undergone constant dynamic reorganization. The results, which are consistent with independent experimental results, suggest a robust mechanism based on ECM-mediated mechanical coupling for collective cell behaviors in 3D ECM.

For the future plan, further substantiate the minimal cell migration model by incorporating more detailed cell-ECM interactions and relevant sub-cellular mechanisms is needed, as well as further investigation of the effects of fiber alignment, ECM mechanical properties and externally applied mechanical cues on collective migration dynamics.
ContributorsNan, Hanqing (Author) / Jiao, Yang (Thesis advisor) / Alford, Terry (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures

Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
This honors thesis is focused on two separate catalysis projects conducted under the mentorship of Dr. Javier Pérez-Ramírez at ETH Zürich. The first project explored ethylene oxychlorination over supported europium oxychloride catalysts. The second project investigated alkyne semihydrogenation over nickel phosphide catalysts. This work is the subject of a publication

This honors thesis is focused on two separate catalysis projects conducted under the mentorship of Dr. Javier Pérez-Ramírez at ETH Zürich. The first project explored ethylene oxychlorination over supported europium oxychloride catalysts. The second project investigated alkyne semihydrogenation over nickel phosphide catalysts. This work is the subject of a publication of which I am a co-author, as cited below.

Project 1 Abstract: Ethylene Oxychlorination
The current two-step process for the industrial process of vinyl chloride production involves CuCl2 catalyzed ethylene oxychlorination to ethylene dichloride followed by thermal cracking of the latter to vinyl chloride. To date, no industrial application of a one-step process is available. To close this gap, this work evaluates a wide range of self-prepared supported CeO2 and EuOCl catalysts for one-step production of vinyl chloride from ethylene in a fixed-bed reactor at 623 773 K and 1 bar using feed ratios of C2H4:HCl:O2:Ar:He = 3:3 6:1.5 6:3:82 89.5. Among all studied systems, CeO2/ZrO2 and CeO2/Zeolite MS show the highest activity but suffer from severe combustion of ethylene, forming COx, while 20 wt.% EuOCl/γ-Al2O3 leads to the best vinyl chloride selectivity of 87% at 15.6% C2H4 conversion with complete suppression of CO2 formation and only 4% selectivity to CO conversion for over 100 h on stream. Characterization by XRD and EDX mapping reveals that much of the Eu is present in non-active phases such as Al2Eu or EuAl4, indicating that alternative synthesis methods could be employed to better utilize the metal. A linear relationship between conversion and metal loading is found for this catalyst, indicating that always part of the used Eu is available as EuOCl, while the rest forms inactive europium aluminate species. Zeolite-supported EuOCl slightly outperforms EuOCl/γ Al2O3 in terms of total yield, but is prone to significant coking and is unstable. Even though a lot of Eu seems locked in inactive species on EuOCl/γ Al2O3, these results indicate possible savings of nearly 16,000 USD per kg of catalyst compared to a bulk EuOCl catalyst. These very promising findings constitute a crucial step for process intensification of polyvinyl chloride production and exploring the potential of supported EuOCl catalysts in industrially-relevant reactions.

Project 2 Abstract: Alkyne Semihydrogenation
Despite strongly suffering from poor noble metal utilization and a highly toxic selectivity modifier (Pb), the archetypal catalyst applied for the three-phase alkyne semihydrogenation, the Pb-doped Pd/CaCO3 (Lindlar catalyst), is still being utilized at industrial level. Inspired by the very recent strategies involving the modification of Pd with p-block elements (i.e., S), this work extrapolates the concept by preparing crystalline metal phosphides with controlled stoichiometry. To develop an affordable and environmentally-friendly alternative to traditional hydrogenation catalysts, nickel, a metal belonging to the same group as Pd and capable of splitting molecular hydrogen has been selected. Herein, a simple two-step synthesis procedure involving nontoxic precursors was used to synthesize bulk nickel phosphides with different stoichiometries (Ni2P, Ni5P4, and Ni12P5) by controlling the P:Ni ratios. To uncover structural and surface features, this catalyst family is characterized with an array of methods including X-ray diffraction (XRD), 31P magic-angle nuclear magnetic resonance (MAS-NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Bulk-sensitive techniques prove the successful preparation of pure phases while XPS analysis unravels the facile passivation occurring at the NixPy surface that persists even after reductive treatment. To assess the characteristic surface fingerprints of these materials, Ar sputtering was carried out at different penetration depths, reveling the presence of Ni+ and P-species. Continuous-flow three-phase hydrogenations of short-chain acetylenic compounds display that the oxidized layer covering the surface is reduced under reaction conditions, as evidenced by the induction period before reaching the steady state performance. To assess the impact of the phosphidation treatment on catalytic performance, the catalysts were benchmarked against a commercial Ni/SiO2-Al2O3 sample. While Ni/SiO2-Al2O3 presents very low selectivity to the alkene (the selectivity is about 10% at full conversion) attributed to the well-known tendency of naked nickel nanoparticles to form hydrides, the performance of nickel phosphides is highly selective and independent of P:Ni ratio. In line with previous findings on PdxS, kinetic tests indicate the occurrence of a dual-site mechanism where the alkyne and hydrogen do not compete for the same site.

This work is the subject of a publication of which I am a co-author, as cited below.

D. Albani; K. Karajovic; B. Tata; Q. Li; S. Mitchell; N. López; J. Pérez-Ramírez. Ensemble Design in Nickel Phosphide Catalysts for Alkyne Semi-Hydrogenation. ChemCatChem 2019. doi.org/10.1002/cctc.201801430
ContributorsTata, Bharath (Author) / Deng, Shuguang (Thesis director) / Muhich, Christopher (Committee member) / Chemical Engineering Program (Contributor, Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Past experiments have revealed several unusual properties about interstitial hydrogen atoms in niobium. Absorption isotherms showed that niobium absorbs a large amount of hydrogen without changing its crystal structure. These isotherms also revealed that the interactions between hydrogen atoms in niobium are a combination of long-range attraction and short-range repulsion

Past experiments have revealed several unusual properties about interstitial hydrogen atoms in niobium. Absorption isotherms showed that niobium absorbs a large amount of hydrogen without changing its crystal structure. These isotherms also revealed that the interactions between hydrogen atoms in niobium are a combination of long-range attraction and short-range repulsion and exhibit many-body characteristics. Other experiments reported the facile thermal diffusion of hydrogen and deuterium in niobium. Contrary to the classical theory of diffusion, these experiments revealed a break in the activation energy of hydrogen diffusion at low temperatures, but no such break was reported for deuterium. Finally, experiments report a phenomenon called electromigration, where hydrogen atoms inside niobium respond to weak electric fields as if they had a positive effective charge. These experimental results date back to when tools like density functional theory (DFT) and modern high-performance computing abilities did not exist. Therefore, the current understanding of these properties is primarily based on inferences from experimental results. Understanding these properties at a deeper level, besides being scientifically important, can profoundly affect various applications involving hydrogen separation and transport. The high-level goal of this work is to use first-principles methods to explain the discussed properties of interstitial hydrogen in niobium. DFT calculations were used to study hydrogen atoms' site preference in niobium and its effect on the cell shape and volume of the host cell. The nature and origin of the interactions between hydrogen atoms were studied through interaction energy, structural, partial charge, and electronic densities of state analysis. A phenomenological model with fewer parameters than traditional models was developed and fit to the experimental absorption data. Thermodynamic quantities such as the enthalpy and entropy of hydrogen dissolution in niobium were derived from this model. The enthalpy of hydrogen dissolution in niobium was also calculated using DFT by sampling different geometric configurations and performing an ensemble-based averaging. Further work is required to explain the observed isotope effects for hydrogen diffusion in niobium and the electromigration phenomena. Applications of the niobium-hydrogen system require studying hydrogen's behavior on niobium's surface.
ContributorsRamcahandran, Arvind (Author) / Lackner, Klaus S. (Thesis advisor) / Zhuang, Houlong (Thesis advisor) / Muhich, Christopher (Committee member) / Singh, Arunima (Committee member) / Arizona State University (Publisher)
Created2021
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Description
For the past two centuries, coal has played a vital role as the primary carbon source, fueling industries and enabling the production of essential carbon-rich materials, including carbon nanotubes, graphite, and diamond. However, the global transition towards sustainable energy production has resulted in a decline in coal usage for energy

For the past two centuries, coal has played a vital role as the primary carbon source, fueling industries and enabling the production of essential carbon-rich materials, including carbon nanotubes, graphite, and diamond. However, the global transition towards sustainable energy production has resulted in a decline in coal usage for energy purposes, with the United States alone witnessing a substantial 50% reduction over the past decade. This shift aligns with the UN’s 2030 sustainability goals, which emphasize the reduction of greenhouse gas emissions and the promotion of cleaner energy sources. Despite the decreased use in energy production, the abundance of coal has sparked interest in exploring its potential for other sustainable and valuable applications.In this context, Direct Ink Writing (DIW) has emerged as a promising additive manufacturing technique that employs liquid or gel-like resins to construct three-dimensional structures. DIW offers a unique advantage by allowing the incorporation of particulate reinforcements, which enhance the properties and functionalities of the materials. This study focuses on evaluating the viability of coal as a sustainable and cost-effective substitute for other carbon-based reinforcements, such as graphite or carbon nanotubes. The research utilizes a thermosetting resin based on phenol-formaldehyde (commercially known as Bakelite) as the matrix, while pulverized coal (250 µm) and carbon black (CB) function as the reinforcements. The DIW ink is meticulously formulated to exhibit shear-thinning behavior, facilitating uniform and continuous printing of structures. Mechanical property testing of the printed structures was conducted following ASTM standards. Interestingly, the study reveals that incorporating a 2 wt% concentration of coal in the resin yields the most significant improvements in tensile modulus and flexural strength, with enhancements of 35% and 12.5% respectively. These findings underscore the promising potential of coal as a sustainable and environmentally friendly reinforcement material in additive manufacturing applications. By harnessing the unique properties of coal, this research opens new avenues for its utilization in the pursuit of greener and more efficient manufacturing processes.
ContributorsSundaravadivelan, Barath (Author) / Song, Kenan (Thesis advisor) / Marvi, Hamidreza (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2023
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Description
High-entropy alloys (HEAs) is a new class of materials which have been studied heavily due to their special mechanical properties. HEAs refers to alloys with multiple equimolar or nearly equimolar elements. HEAs show exceptional and attractive properties currently absent from conventional alloys, which make them the center of intense investigation.

High-entropy alloys (HEAs) is a new class of materials which have been studied heavily due to their special mechanical properties. HEAs refers to alloys with multiple equimolar or nearly equimolar elements. HEAs show exceptional and attractive properties currently absent from conventional alloys, which make them the center of intense investigation. HEAs obtain their properties from four core effects that they exhibit and most of the work on them have been dedicated to study their mechanical properties. In contrast, little or no research have gone into studying the functional or even thermal properties of HEAs. Some HEAs have also shown exceptional or very high melting points. According to the definition of HEAs, Si-Ge-Sn alloys with equal or comparable concentrations of the three group IV elements belong to the category of HEAs. Thus, the equimolar components of Si-Ge-Sn alloys probably allow their atomic structures to display the same fundamental effects of metallic HEAs. The experimental fabrication of such alloys has been proven to be very difficult, which is mainly due to differences between the properties of their constituent elements, as indicated from their binary phase diagrams. However, previous computational studies have shown that SiGeSn HEAs have some very interesting properties, such as high electrical conductivity, low thermal conductivity and semiconducting properties. In this work, going for a complete characterization of the SiGeSn HEA properties, the melting point of this alloy is studied using classical molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The aim is to investigate the effects of high Sn content in this alloy on the melting point compared with the traditional SiGe alloys. Classical MD simulations results strongly indicates that none of the available empirical potentials is able to predict accurate or reasonable melting points for SiGeSn HEAs and most of its subsystems. DFT calculations results show that SiGeSn HEA have a melting point which represent the mean value of its constituent elements and that no special deviations are found. This work contributes to the study of SiGeSn HEA properties, which can serve as guidance before the successful experimental fabrication of this alloy.
ContributorsAlqaisi, Ahmad Madhat Odeh (Author) / Hong, Qi-Jun (Thesis advisor) / Zhuang, Houlong (Thesis advisor) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2023
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This study presents an evaluation of the predicted flow behavior and the minimum outlet diameter in a computationally simulated hopper. The flow pattern in hoppers was simulated to test three size fractions, three moisture levels of microcrystalline cellulose (MCC), and two hopper wall angles in Multiphase Flow with Interphase eXchanges

This study presents an evaluation of the predicted flow behavior and the minimum outlet diameter in a computationally simulated hopper. The flow pattern in hoppers was simulated to test three size fractions, three moisture levels of microcrystalline cellulose (MCC), and two hopper wall angles in Multiphase Flow with Interphase eXchanges (MFiX). Predictions from MFiX were then compared to current literature. As expected, the smaller size fractions with lower water content were closer to ideal funnel flow than their larger counterparts. The predicted minimum outlet diameter in simulations showed good agreement with close to ideal flowability. These findings illustrate the connection between lab flowability experiments and computational simulations. Lastly, three fluidized bed simulations were also created in MFiX with zeolite 13X to analyze the pressure and velocity within the bed. The application of flowability simulations can improve the transport of solids in processing equipment used during the production of powders.
ContributorsBuchanan, Lidija (Author) / Emady, Heather (Thesis advisor) / Muhich, Christopher (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2023
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Interfacial interactions between materials in complex heterostructures can dominate the material's response in manymodern-day energy-related devices and processes. Considerable research has been dedicated towards addressing the profound effects of interfaces. Here, first-principles-based quantum mechanical simulations are discussed to characterize the interfacial materials properties of two systems. First, density-functional theory (DFT) calculations were performed

Interfacial interactions between materials in complex heterostructures can dominate the material's response in manymodern-day energy-related devices and processes. Considerable research has been dedicated towards addressing the profound effects of interfaces. Here, first-principles-based quantum mechanical simulations are discussed to characterize the interfacial materials properties of two systems. First, density-functional theory (DFT) calculations were performed for ceramic oxide grain boundaries in undoped and doped CeO2. Second, the development, theoretical framework, and utilization of high-throughput, workflow-based, DFT calculations are presented to model the synthesis of two-dimensional (2D) heterostructured materials. Utilizing this workflow, predictive machine learning models were created to elucidate key interface-property relationships in 2D heterostructured materials. The DFT simulations reveal that the Σ3(111)/[101] grain boundary was energetically more stable than theΣ3(121)/[101]grain boundary due to the larger atomic coherency in the Σ3(111)/[101] grain boundary plane. The alkaline-earth metal-doped grain boundary energies demonstrate a parabolic dependence on the size of the solutes, interfacial strain, and packing density of the grain boundary. The grain boundary energies were stabilized upon Ca, Sr, and Ba doping whereas Be and Mg render them energetically unstable. The electronic density of states reveals that no defect states were present in/above the band gap. The thermodynamic trapping of oxygen vacancies in the near grain boundary region was not significantly impacted by the presence of Ca-solute ions. However, the migration energy barriers within the grain boundary core were dramatically reduced with high local Ca-solute concentrations, around 0.3 eV-0.5 eV. Chapter 5 and Chapter 6 discusses the development of the open-source, high-throughput computational "synthesis"based workflow package Hetero2d and the application of Hetero2d using 52 Janus 2D materials and 19 metallic, cubic phase, elemental substrates. The 438 Janus 2D-substrate pairs were analyzed by identifying substrate surfaces that stabilize metastable Janus 2D materials, characterizing their effects on the post-adsorbed 2D materials, and identifying the bonding between the 2D material and substrate. Machine learning models were applied to predict the binding energy, z-separation, and charge transfer of the Janus 2D-substrate pairs providing insight into the critical properties which factor into these properties.
ContributorsBoland, Tara Maria (Author) / Crozier, Peter A (Thesis advisor) / Singh, Arunima K (Thesis advisor) / Rez, Peter (Committee member) / Muhich, Christopher (Committee member) / Dholabhai, Pratik (Committee member) / Arizona State University (Publisher)
Created2022
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Siloxane, a common contaminant present in biogas, is known for adverse effects on cogeneration prime movers. In this work, the solid oxide fuel cell (SOFC) nickel-yttria stabilized zirconia (Ni-YSZ) anode degradation due to poisoning by siloxane was investigated. For this purpose, experiments with different fuels, different deposition substrate materials, different

Siloxane, a common contaminant present in biogas, is known for adverse effects on cogeneration prime movers. In this work, the solid oxide fuel cell (SOFC) nickel-yttria stabilized zirconia (Ni-YSZ) anode degradation due to poisoning by siloxane was investigated. For this purpose, experiments with different fuels, different deposition substrate materials, different structure of contamination siloxane (cyclic and linear) and entire failure process are conducted in this study. The electrochemical and material characterization methods, such as Electrochemical Impedance Spectroscopy (EIS), Scanning Electron Microscope- Wavelength Dispersive Spectrometers (SEM-WDS), X-ray Photoelectron Spectroscopy (XPS), X-ray Diffraction (XRD), and Raman spectroscopy, were applied to investigate the anode degradation behavior. The electrochemical characterization results show that the SOFCs performance degradation caused by siloxane contamination is irreversible under bio-syngas condition. An equivalent circuit model (ECM) is developed based on electrochemical characterization results. Based on the Distribution of Relaxation Time (DRT) method, the detailed microstructure parameter changes are evaluated corresponding to the ECM results. The results contradict the previously proposed siloxane degradation mechanism as the experimental results show that water can inhibit anode deactivation. For anode materials, Ni is considered a major factor in siloxane deposition reactions in Ni-YSZ anode. Based on the results of XPS, XRD and WDS analysis, an initial layer of carbon deposition develops and is considered a critical process for the siloxane deposition reaction. Based on the experimental results in this study and previous studies about siloxane deposition on metal oxides, the proposed siloxane deposition process occurs in stages consisting of the siloxane adsorption, initial carbon deposition, siloxane polymerization and amorphous silicon dioxide deposition.
ContributorsTian, Jiashen (Author) / Milcarek, Ryan J. (Thesis advisor) / Muhich, Christopher (Committee member) / Wang, Liping (Committee member) / Phelan, Patrick (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2022