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- All Subjects: Materials Science
- Creators: Zhuang, Houlong
Description
Single-layer pentagonal materials have received limited attention compared with their counterparts with hexagonal structures. They are two-dimensional (2D) materials with pentagonal structures, that exhibit novel electronic, optical, or magnetic properties. There are 15 types of pentagonal tessellations which allow plenty of options for constructing 2D pentagonal lattices. Few of them have been explored theoretically or experimentally. Studying this new type of 2D materials with density functional theory (DFT) will inspire the discovery of new 2D materials and open up applications of these materials in electronic and magnetic devices.In this dissertation, DFT is applied to discover novel 2D materials with pentagonal structures. Firstly, I examine the possibility of forming a 2D nanosheet with the vertices of type 15 pentagons occupied by boron, silicon, phosphorous, sulfur, gallium, germanium or tin atoms. I obtain different rearranged structures such as a single-layer gallium sheet with triangular patterns. Then the exploration expands to other 14 types of pentagons, leading to the discoveries of carbon nanosheets with Cairo tessellation (type 2/4 pentagons) and other patterns. The resulting 2D structures exhibit diverse electrical properties. Then I reveal the hidden Cairo tessellations in the pyrite structures and discover a family of planar 2D materials (such as PtP2), with a chemical formula of AB2 and space group pa ̄3. The combination of DFT and geometries opens up a novel route for the discovery of new 2D materials. Following this path, a series of 2D pentagonal materials such as 2D CoS2 are revealed with promising electronic and magnetic applications. Specifically, the DFT calculations show that CoS2 is an antiferromagnetic semiconductor with a band gap of 2.24 eV, and a N ́eel temperature of about 20 K. In order to enhance the superexchange interactions between the ions in this binary compound, I explore the ternary 2D pentagonal material CoAsS, that lacks the inversion symmetry. I find out CoAsS exhibits a higher Curie temperature of 95 K and a sizable piezoelectricity (d11=-3.52 pm/V). In addition to CoAsS, 34 ternary 2D pentagonal materials are discovered, among which I focus on FeAsS, that is a semiconductor showing strong magnetocrystalline anisotropy and sizable Berry curvature. Its magnetocrystalline anisotropy energy is 440 μeV/Fe ion, higher than many other 2D magnets that have been found.
Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices.
Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices.
ContributorsLiu, Lei (Author) / Zhuang, Houlong (Thesis advisor) / Singh, Arunima (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
Description
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.
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
Description
Corrosion fatigue has been of prime concern in railways, aerospace, construction industries and so on. Even in the case of many medical equipment, corrosion fatigue is considered to be a major challenge. The fact that even high strength materials have lower resistance to corrosion fatigue makes it an interesting area for research. The analysis of propagation of fatigue crack growth under environmental interaction and the life prediction is significant to reduce the maintenance costs and assure structural integrity. Without proper investigation of the crack extension under corrosion fatigue, the scenario can lead to catastrophic disasters due to premature failure of a structure. An attempt has been made in this study to predict the corrosion fatigue crack growth with reasonable accuracy. Models that have been developed so far predict the crack propagation for constant amplitude loading (CAL). However, most of the industrial applications encounter random loading. Hence there is a need to develop models based on time scale. An existing time scale model that can predict the fatigue crack growth for constant and variable amplitude loading (VAL) in the Paris region is initially modified to extend the prediction to near threshold and unstable crack growth region. Extensive data collection was carried out to calibrate the model for corrosion fatigue crack growth (CFCG) based on the experimental data. The time scale model is improved to incorporate the effect of corrosive environments such as NaCl and dry hydrogen in the fatigue crack growth (FCG) by investigation of the trend in change of the crack growth. The time scale model gives the advantage of coupling the time phenomenon stress corrosion cracking which is suggested as a future work in this paper.
ContributorsKurian, Bianca (Author) / Liu, Yongming (Thesis advisor) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
This research seeks to answer the question if there is a singular relationship between stishovite nucleation and the atomistic structure of the preshocked amorphous SiO$_2$. To do this a stishovite manufacturing method is developed in which 1,152 samples were produced. The majority of these samples did crystallize. The method was produced through two rounds of experiments and fine-tuning with the pressure damp, temperature damp, shock pressure using an NPHug fix, and sample origin. A new random atomic insertion method was used to generate a new and different SiO$_2$ amorphous structure not before seen within the research literature. The optimal values for shock were found to be 60~GPa for randomly atom insertion samples and 55~GPa for quartz origin samples. Temperature damp appeared to have a slight effect optimizing at 0.05~ps and the pressure damp had no visible effect, testing was done with temperature damp from 0.05 to 0.5~ps and pressure damp from 0.1 to 10.0~ps. There appeared to be significant randomness in crystallization behavior. The preshocked and postnucleated samples were transformed into Gaussian fields of crystal, mass, and charge. These fields were divided and classified using a cut-off method taking the number of crystals produced in portions of each simulation and classifying each potion as nucleated or non-nucleated. Data in which some nucleation but not a critical amount was present was removed constituting 2.6\% to 20.3\% of data in all tests. A max method was also used which takes only the maximum portions of each simulation to classify as nucleating. There are three other variables tested within this work, a sample size of 18,000 or 72,728~atoms, Gaussian variance of 1 or 4~\AA, and Convolutional neural network (CNN) architecture of a garden verity or all convolution along with the portioning classification method, sample origination, and Gaussian field type. In total 64 tests were performed to try every combination of variable. No significant classifications were made by the CNNs to nucleation or non-nucleation portions. The results clearly confirmed that the data was not abstracting to atomistic structure and was random by all classifications of the CNNs. The all convolution CNN testing did show smoother outcomes in training with less fluctuations. 59\% of all validation accuracy was held at 0.5 for a random state and 84\% was within $\pm0.02$ of 0.5. It is conclusive that prenucleation structure is not the sole predictor of nucleation behavior. It is not conclusive if prenucleation structure is a partial or non-factor within nucleation of stishovite from amorphous SiO$_2$.
ContributorsChristen, Jonathan Scorr (Author) / Oswald, Jay (Thesis advisor) / Muhich, Christopher (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
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 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
Current Li-ion battery technologies are limited by the low capacities of theelectrode materials and require developments to meet stringent performance demands for
future energy storage devices. Electrode materials that alloy with Li, such as Si, are one
of the most promising alternatives for Li-ion battery anodes due to their high capacities.
Tetrel (Si, Ge, Sn) clathrates are a class of host-guest crystalline structures in which
Tetrel elements form a cage framework and encapsulate metal guest atoms. These
structures can form with defects such as framework/guest atom substitutions and
vacancies which result in a wide design space for tuning materials properties. The goal of
this work is to establish structure property relationships within the context of Li-ion
battery anode applications. The type I Ba 8 Al y Ge 46-y clathrates are investigated for their
electrochemical reactions with Li and show high capacities indicative of alloying
reactions. DFT calculations show that Li insertion into the framework vacancies is
favorable, but the migration barriers are too high for room temperature diffusion. Then,
guest free type I clathrates are investigated for their Li and Na migration barriers. The
results show that Li migration in the clathrate frameworks have low energy barriers (0.1-
0.4 eV) which suggest the possibility for room temperature diffusion. Then, the guest
free, type II Si clathrate (Na 1 Si 136 ) is synthesized and reversible Li insertion into the type
II Si clathrate structure is demonstrated. Based on the reasonable capacity (230 mAh/g),
low reaction voltage (0.30 V) and low volume expansion (0.21 %), the Si clathrate could
be a promising insertion anode for Li-ion batteries. Next, synchrotron X-ray
measurements and pair distribution function (PDF) analysis are used to investigate the
lithiation pathways of Ba 8 Ge 43 , Ba 8 Al 16 Ge 30 , Ba 8 Ga 15 Sn 31 and Na 0.3 Si 136 . The results
show that the Ba-clathrates undergo amorphous phase transformations which is distinct
from their elemental analogues (Ge, Sn) which feature crystalline lithiation pathways.
Based on the high capacities and solid-solution reaction mechanism, guest-filled
clathrates could be promising precursors to form alloying anodes with novel
electrochemical properties. Finally, several high temperature (300-550 °C)
electrochemical synthesis methods for Na-Si and Na-Ge clathrates are demonstrated in a
cell using a Na β’’-alumina solid electrolyte.
ContributorsDopilka, Andrew (Author) / Chan, Candace K (Thesis advisor) / Zhuang, Houlong (Committee member) / Peng, Xihong (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2021
Description
Metal/ceramic coatings and medium-entropy alloys or high-entropy alloys have received lots of attention due to their outstanding mechanical properties and resistance of corrosion compared to traditional coatings and alloys. Both materials can be designed by adding new elements from their base elements, which present great design opportunities and open up many new structural and functional applications. However, theoretical modeling and simulation by density functional theory (DFT) and classical interatomic potential in both systems are challenging due to the large number of chemical interactions between atoms, and first-principles Monte-Carlo simulation is an expensive computation. With the development of machine learning potential, especially for the descriptors that can describe complex patterns of atomic structures and can be used by neural networks, combining the emerging database of high-quality DFT calculations and efficient algorithms make the machine learning a potential way to solve the aforementioned challenges, though the design of the descriptor sometimes is painstaking, besides, the model is a black box that is hard to understand, and the training of neural network is time-consuming as well. Therefore, three studies are listed in this dissertation to study and mitigate the problem mentioned above by using machine learning. The first study uses a crystal graph convolutional neural network framework combined with reinforcement learning to efficiently find optimal structures of TiAl/TiAlN interface that have high work of adhesion. The second study uses a crystal graph convolutional neural network to efficiently investigate the energy and short-range order of Si0.33Ge0.33Sn0.33 medium entropy alloys. The last study introduces an interpretable regression-trees-based ensemble learning approach that can efficiently predict the properties of structures like carbons with a small size of data to relieve the time-consuming problem of training.
ContributorsJiang, Xinyu (Author) / Zhuang, Houlong (Thesis advisor) / Nian, Qiong (Thesis advisor) / Hong, Qijun (Committee member) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2024
Description
Magnetic textures, like skyrmions, merons, and domain walls are predicted to be future for the next-generation data-storage and information-transfer technologies due to their ultrafast spin-switching capabilities. However, most of these textures exist at low temperatures which is an issue for these applications. This thesis studies room temperature topological magnetic materials using Chromium telluride (CrTe2) and iron gallium telluride (Fe3GaTe2) as a model system via a combination of single-crystal synthesis, experimental structural, and magnetic characterization. The scientific knowledge gained by this work will be useful in designing unique topological textures beyond traditional Skyrmions to merons, bi-skyrmions, etc. which would be useful in improving energy-efficient storage solutions and advancing computational technologies for the future.
ContributorsMujumdar, Kshitish Raghavendra (Author) / Susarla, Sandhya (Thesis advisor) / Zhuang, Houlong (Thesis advisor) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2024
Description
2D materials with reduced symmetry have gained great interest in the past decade due to the arising quantum properties introduced by the structural asymmetry. A particular example is called 2D Janus materials. Named after Roman god Janus with two faces, Janus materials have different chemical compositions on the two sides of materials, leading to a structure with broken mirror symmetry. Electronegativity difference of the facial elements induces a built-in polarization field pointing out of the plane, which has driven a lot of theory predictions on Rashba splitting, high- temperature ferromagnetism, Skyrmion formation, and so on. Previously reported experimental synthesis of Janus 2D materials relies on high-temperature processing, which limits the crystallinity of as produced 2D layers. In this dissertation, I present a room temperature selective epitaxial atomic re- placement (SEAR) method to convert CVD-grown transition metal dichalcogenides (TMDs) into a Janus structure. Chemically reactive H2 plasma is used to selectively etch off the top layer of chalcogen atoms and the introduction of replacement chalco- gen source in-situ allows for the achievement of Janus structures in one step at room temperature. It is confirmed that the produced Janus monolayers possess high crys- tallinity and good excitonic properties. Moving forward, I show the fabrication of lateral and vertical heterostructures of Janus materials, which are predicted to show exotic properties because of the intrinsic polarization field. To efficiently screen other kinds of interesting Janus structures, a new plasma chamber is designed to allow in-situ optical measurement on the target monolayer during the SEAR process. Successful conversion is seen on mechanically exfoliated MoSe2 and WSe2, and insights into reaction kinetics are gain from Raman spectra evolution. Using the monitoring ability, Janus SNbSe is synthesized for the first time. It’s also demonstrated that the overall crystallinity of as produced Janus monolayer
SWSe and SMoSe are correlated with the source of monolayer TMDs.
Overall, the synthesis of the Janus monolayers using the described method paves the way to the production of highly crystalline Janus materials, and with the in-situ monitoring ability, a deeper understanding of the mechanism is reached. This will accelerate future exploration of other Janus materials synthesis, and confirmation and discovery of their exciting quantum properties.
ContributorsQin, Ying (Author) / Tongay, Sefaattin (Thesis advisor) / Zhuang, Houlong (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
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 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