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This thesis focuses on the theoretical work done to determine thermodynamic properties of a chalcopyrite thin-film material for use as a photovoltaic material in a tandem device. The material of main focus here is ZnGeAs2, which was chosen for the relative abundance of constituents, favorable photovoltaic properties, and good lattice

This thesis focuses on the theoretical work done to determine thermodynamic properties of a chalcopyrite thin-film material for use as a photovoltaic material in a tandem device. The material of main focus here is ZnGeAs2, which was chosen for the relative abundance of constituents, favorable photovoltaic properties, and good lattice matching with ZnSnP2, the other component in this tandem device. This work is divided into two main chapters, which will cover: calculations and method to determine the formation energy and abundance of native point defects, and a model to calculate the vapor pressure over a ternary material from first-principles. The purpose of this work is to guide experimental work being done in tandem to synthesize ZnGeAs2 in thin-film form with high enough quality such that it can be used as a photovoltaic. Since properties of photovoltaic depend greatly on defect concentrations and film quality, a theoretical understanding of how laboratory conditions affect these properties is very valuable. The work done here is from first-principles and utilizes density functional theory using the local density approximation. Results from the native point defect study show that the zinc vacancy (VZn) and the germanium antisite (GeZn) are the more prominent defects; which most likely produce non-stoichiometric films. The vapor pressure model for a ternary system is validated using known vapor pressure for monatomic and binary test systems. With a valid ternary system vapor pressure model, results show there is a kinetic barrier to decomposition for ZnGeAs2.
ContributorsTucker, Jon R (Author) / Van Schilfgaarde, Mark (Thesis advisor) / Newman, Nathan (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2011
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Description
In 2022, integrated circuit interconnects will approach 10 nm and the diffusion barrier layers needed to ensure long lasting devices will be at 1 nm. This dimension means the interconnect will be dominated by the interface and it has been shown the interface is currently eroding device performance. The standard

In 2022, integrated circuit interconnects will approach 10 nm and the diffusion barrier layers needed to ensure long lasting devices will be at 1 nm. This dimension means the interconnect will be dominated by the interface and it has been shown the interface is currently eroding device performance. The standard interconnect system has three layers - a Copper metal core, a Tantalum Adhesion layer and a Tantalum Nitride Diffusion Barrier Layer. An alternate interconnect schema is a Tantalum Nitride barrier layer and Silver as a metal. The adhesion layer is removed from the system along with changing to an alternate, low resistivity metal. First principles are used to assess the interface of the Silver and Tantalum Nitride. Several stoichiometric 1:1 Tantalum Nitride polymorphs are assessed and it is found that the Fe2P crystal structure is actually the most stable crystal structure which is at odds with the published phase diagram for ambient crystal structure. The surface stability of Fe2P-TaN is assessed and the absorption enthalpy of Silver adatoms is calculated. Finally, the thermodynamic stability of the TaN-Ag interconnect system is assessed.
ContributorsGrumski, Michael (Author) / Adams, James (Thesis advisor) / Krause, Stephen (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2012
Description

Graph neural networks (GNN) offer a potential method of bypassing the Kohn-Sham equations in density functional theory (DFT) calculations by learning both the Hohenberg-Kohn (HK) mapping of electron density to energy, allowing for calculations of much larger atomic systems and time scales and enabling large-scale MD simulations with DFT-level accuracy.

Graph neural networks (GNN) offer a potential method of bypassing the Kohn-Sham equations in density functional theory (DFT) calculations by learning both the Hohenberg-Kohn (HK) mapping of electron density to energy, allowing for calculations of much larger atomic systems and time scales and enabling large-scale MD simulations with DFT-level accuracy. In this work, we investigate the feasibility of GNNs to learn the HK map from the external potential approximated as Gaussians to the electron density 𝑛(𝑟), and the mapping from 𝑛(𝑟) to the energy density 𝑒(𝑟) using Pytorch Geometric. We develop a graph representation for densities on radial grid points and determine that a k-nearest neighbor algorithm for determining node connections is an effective approach compared to a distance cutoff model, having an average graph size of 6.31 MB and 32.0 MB for datasets with 𝑘 = 10 and 𝑘 = 50 respectively. Furthermore, we develop two GNNs in Pytorch Geometric, and demonstrate a decrease in training losses for a 𝑛(𝑟) to 𝑒(𝑟) of 8.52 · 10^14 and 3.10 · 10^14 for 𝑘 = 10 and 𝑘 = 20 datasets respectively, suggesting the model could be further trained and optimized to learn the electron density to energy functional.

ContributorsHayes, Matthew (Author) / Muhich, Christopher (Thesis director) / Oswald, Jay (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2023-05
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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
Description

Using DFT calculations and GAMESS computational software, porphine and its derivatives were analyzed for unique sites to accept the adsorbates As(III), As(V) and P(V) in order to compare resulting adsorption energies and determine if any of these molecules prefer arsenic oxyanions over phosphate. Pure porphine preferred As(III) over P(V) with

Using DFT calculations and GAMESS computational software, porphine and its derivatives were analyzed for unique sites to accept the adsorbates As(III), As(V) and P(V) in order to compare resulting adsorption energies and determine if any of these molecules prefer arsenic oxyanions over phosphate. Pure porphine preferred As(III) over P(V) with a resulting adsorption energy of -0.7974 eV. Of the functionalized porphyrins tested, carboxyl porphyrin preferred As(V) over P(V) with a total adsorption energy of -0.7345 eV. Ethyl, methyl, chlorine and amino porphyrin all preferred As(III), with energies of -0.7934, -0.8239, -0.7602, and -0.8508 eV, respectively. Of the metalated porphyrins tested, copper and vanadium porphyrin preferred As(V) over P(V) with adsorption energies of -0.7645 and -2.0915 eV. Chromium, iron and magnesium porphyrin all preferred As(III) over P(V) with energies of -0.5993, -1.4539, and - 1.0790 eV, respectively.

ContributorsKusbel, Ashley (Author) / Muhich, Christopher (Thesis director) / Jin, Kailong (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor)
Created2023-05
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Description
Losses in commercial microwave dielectrics arise from spin excitations in paramagnetic transition metal dopants, at least at reduced temperatures. The magnitude of the loss tangent can be altered by orders of magnitude through the application of an external magnetic field. The goal of this thesis is to produce “smart” dielectrics

Losses in commercial microwave dielectrics arise from spin excitations in paramagnetic transition metal dopants, at least at reduced temperatures. The magnitude of the loss tangent can be altered by orders of magnitude through the application of an external magnetic field. The goal of this thesis is to produce “smart” dielectrics that can be switched “on” or “off” at small magnetic fields while investigating the influence of transition metal dopants on the dielectric, magnetic, and structural properties.

A proof of principle demonstration of a resonator that can switch from a high-Q “on state” to a low-Q “off state” at reduced temperatures is demonstrated in (Al1-xFex)2O3 and La(Al1-xFex)O3. The Fe3+ ions are in a high spin state (S=5/2) and undergo electron paramagnetic resonance absorption transitions that increase the microwave loss of the system. Transitions occur between mJ states with a corresponding change in the angular momentum, J, by ±ħ (i.e., ΔmJ=±1) at small magnetic fields. The paramagnetic ions also have an influence on the dielectric and magnetic properties, which I explore in these systems along with another low loss complex perovskite material, Ca[(Al1-xFex)1/2Nb1/2]O3. I describe what constitutes an optimal microwave loss switchable material induced from EPR transitions and the mechanisms associated with the key properties.

As a first step to modeling the properties of high-performance microwave host lattices and ultimately their performance at microwave frequencies, a first-principles approach is used to determine the structural phase stability of various complex perovskites with a range of tolerance factors at 0 K and finite temperatures. By understanding the correct structural phases of these complex perovskites, the temperature coefficient of resonant frequency can be better predicted.

A strong understanding of these parameters is expected to open the possibility to produce new types of high-performance switchable filters, time domain MIMO’s, multiplexers, and demultiplexers.
ContributorsGonzales, Justin Michael (Author) / Newman, Nathan (Thesis advisor) / Muhich, Christopher (Committee member) / Tongay, Sefaattin (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Functional materials can be characterized as materials that have tunable properties and are attractive solutions to the improvement and optimization of processes that require specific physiochemical characteristics. Through tailoring and altering these materials, their characteristics can be fine-tuned for specific applications. Computational modeling proves to be a crucial methodology in

Functional materials can be characterized as materials that have tunable properties and are attractive solutions to the improvement and optimization of processes that require specific physiochemical characteristics. Through tailoring and altering these materials, their characteristics can be fine-tuned for specific applications. Computational modeling proves to be a crucial methodology in the design and optimization of such materials. This dissertation encompasses the utilization of molecular dynamics simulations and quantum calculations in two fields of functional materials: electrolytes and semiconductors. Molecular dynamics (MD) simulations were performed on ionic liquid-based electrolyte systems to identify molecular interactions, structural changes, and transport properties that are often reflected in experimental results. The simulations aid in the development process of the electrolyte systems in terms of concentrations of the constituents and can be invoked as a complementary or predictive tool to laboratory experiments. The theme of this study stretches further to include computational studies of the reactivity of atomic layer deposition (ALD) precursors. Selected aminosilane-based precursors were chosen to undergo density functional theory (DFT) calculations to determine surface reactivity and viability in an industrial setting. The calculations were expanded to include the testing of a semi-empirical tight binding program to predict growth per cycle and precursor reactivity with a high surface coverage model. Overall, the implementation of computational methodologies and techniques within these applications improves materials design and process efficiency while streamlining the development of new functional materials.
ContributorsGliege, Marisa Elise (Author) / Dai, Lenore (Thesis advisor) / Derecskei-Kovacs, Agnes (Thesis advisor) / Muhich, Christopher (Committee member) / Emady, Heather (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021