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Description
he accurate simulation of many-body quantum systems is a challenge for computational physics. Quantum Monte Carlo methods are a class of algorithms that can be used to solve the many-body problem. I study many-body quantum systems with Path Integral Monte Carlo techniques in three related areas of semiconductor physics: (1)

he accurate simulation of many-body quantum systems is a challenge for computational physics. Quantum Monte Carlo methods are a class of algorithms that can be used to solve the many-body problem. I study many-body quantum systems with Path Integral Monte Carlo techniques in three related areas of semiconductor physics: (1) the role of correlation in exchange coupling of spins in double quantum dots, (2) the degree of correlation and hyperpolarizability in Stark shifts in InGaAs/GaAs dots, and (3) van der Waals interactions between 1-D metallic quantum wires at finite temperature. The two-site model is one of the simplest quantum problems, yet the quantitative mapping from a three-dimensional model of a quantum double dot to an effective two-site model has many subtleties requiring careful treatment of exchange and correlation. I calculate exchange coupling of a pair of spins in a double dot from the permutations in a bosonic path integral, using Monte Carlo method. I also map this problem to a Hubbard model and find that exchange and correlation renormalizes the model parameters, dramatically decreasing the effective on-site repulsion at larger separations. Next, I investigated the energy, dipole moment, polarizability and hyperpolarizability of excitonic system in InGaAs/GaAs quantum dots of different shapes and successfully give the photoluminescence spectra for different dots with electric fields in both the growth and transverse direction. I also showed that my method can deal with the higher-order hyperpolarizability, which is most relevant for fields directed in the lateral direction of large dots. Finally, I show how van der Waals interactions between two metallic quantum wires change with respect to the distance between them. Comparing the results from quantum Monte Carlo and the random phase approximation, I find similar power law dependance. My results for the calculation in quasi-1D and exact 1D wires include the effect of temperature, which has not previously been studied.
ContributorsZhang, Lei (Author) / Shumway, John (Thesis advisor) / Schmidt, Kevin (Committee member) / Bennet, Peter (Committee member) / Menéndez, Jose (Committee member) / Drucker, Jeff (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Human-robot interactions can often be formulated as general-sum differential games where the equilibrial policies are governed by Hamilton-Jacobi-Isaacs (HJI) equations. Solving HJI PDEs faces the curse of dimensionality (CoD). While physics-informed neural networks (PINNs) alleviate CoD in solving PDEs with smooth solutions, they fall short in learning discontinuous solutions due

Human-robot interactions can often be formulated as general-sum differential games where the equilibrial policies are governed by Hamilton-Jacobi-Isaacs (HJI) equations. Solving HJI PDEs faces the curse of dimensionality (CoD). While physics-informed neural networks (PINNs) alleviate CoD in solving PDEs with smooth solutions, they fall short in learning discontinuous solutions due to their sampling nature. This causes PINNs to have poor safety performance when they are applied to approximate values that are discontinuous due to state constraints. This dissertation aims to improve the safety performance of PINN-based value and policy models. The first contribution of the dissertation is to develop learning methods to approximate discontinuous values. Specifically, three solutions are developed: (1) hybrid learning uses both supervisory and PDE losses, (2) value-hardening solves HJIs with increasing Lipschitz constant on the constraint violation penalty, and (3) the epigraphical technique lifts the value to a higher-dimensional state space where it becomes continuous. Evaluations through 5D and 9D vehicle and 13D drone simulations reveal that the hybrid method outperforms others in terms of generalization and safety performance. The second contribution is a learning-theoretical analysis of PINN for value and policy approximation. Specifically, by extending the neural tangent kernel (NTK) framework, this dissertation explores why the choice of activation function significantly affects the PINN generalization performance, and why the inclusion of supervisory costate data improves the safety performance. The last contribution is a series of extensions of the hybrid PINN method to address real-time parameter estimation problems in incomplete-information games. Specifically, a Pontryagin-mode PINN is developed to avoid costly computation for supervisory data. The key idea is the introduction of a costate loss, which is cheap to compute yet effectively enables the learning of important value changes and policies in space-time. Building upon this, a Pontryagin-mode neural operator is developed to achieve state-of-the-art (SOTA) safety performance across a set of differential games with parametric state constraints. This dissertation demonstrates the utility of the resultant neural operator in estimating player constraint parameters during incomplete-information games.
ContributorsZhang, Lei (Author) / Ren, Yi (Thesis advisor) / Si, Jennie (Committee member) / Berman, Spring (Committee member) / Zhang, Wenlong (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2024
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Description
Small and medium-sized enterprises (SMEs) have emerged as a vital force in the economic development of our country, significantly influencing national economic growth, employment rates, market competition, and innovation. Consequently, the ability of SMEs to achieve stable performance growth is crucial for socio-economic development. Previous research has identified factors such

Small and medium-sized enterprises (SMEs) have emerged as a vital force in the economic development of our country, significantly influencing national economic growth, employment rates, market competition, and innovation. Consequently, the ability of SMEs to achieve stable performance growth is crucial for socio-economic development. Previous research has identified factors such as political connections, cash flow, capital, and information technology as significant contributors to business growth. However, SMEs often lack these resources or cannot control them, making existing research inadequate for guiding the performance growth of SMEs.To address this issue, this study is grounded in the resource-based view and constructs a theoretical model on the impact of SME strategic completeness on performance growth. This model is based on literature research and in-depth interviews. It highlights the mediating roles of market adaptability, operational agility, and employee proactivity. Additionally, the model examines the moderating effects of competitive intensity, strategic implementation capability, and management digitalization. The study collected 203 valid SME samples for analysis and hypothesis testing, yielding the following conclusions: (1)The more comprehensive the business strategy, the better the adaptability to external markets, the higher the operational agility, and the stronger the initiative of employees. (2)Better market adaptability leads to faster performance growth. (3)Higher operational agility accelerates performance growth. (4)Greater employee initiative enhances performance growth. (5)The stronger the external competitive intensity faced by a business, the more effective a well-developed strategy is in improving market adaptability, operational agility, and employee initiative. (6)Stronger strategic implementation capabilities further enhance the effectiveness of a well-developed strategy in improving market adaptability and employee initiative. (7)A higher level of management digitalization enhances the effects of market adaptability, operational agility, and employee initiative, thereby boosting business performance. This study offers theoretical and practical value by clarifying the paths, mechanisms, and boundary conditions through which strategic completeness promotes business performance growth, enriching the theoretical system of SME performance growth. Furthermore, by integrating the cutting-edge concept of management digitalization into the research on strategic completeness and performance growth, this study contributes to the development and refinement of the research framework. Practically, it provides strategic recommendations for SMEs on how to enhance business performance growth through strategic completeness.
ContributorsZhang, Lei (Author) / Wang, Lili (Thesis advisor) / Guo, Qigui (Thesis advisor) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2024
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Description
Modular multilevel converters (MMCs) have become an attractive technology for high power applications. One of the main challenges associated with control and operation of the MMC-based systems is to smoothly precharge submodule (SM) capacitors to the nominal voltage during the startup process. The existing closed-loop methods require additional effort to

Modular multilevel converters (MMCs) have become an attractive technology for high power applications. One of the main challenges associated with control and operation of the MMC-based systems is to smoothly precharge submodule (SM) capacitors to the nominal voltage during the startup process. The existing closed-loop methods require additional effort to analyze the small-signal model of MMC and tune control parameters. The existing open-loop methods require auxiliary voltage sources to charge SM capacitors, which add to the system complexity and cost. A generalized precharging strategy is proposed in this thesis.

For large-scale MMC-embedded power systems, it is required to investigate dynamic performance, fault characteristics, and stability. Modeling of the MMC is one of the challenges associated with the study of large-scale MMC-based power systems. The existing models of MMC did not consider the various configurations of SMs and different operating conditions. An improved equivalent circuit model is proposed in this thesis.

The solid state transformer (SST) has been investigated for the distribution systems to reduce the volume and weight of power transformer. Recently, the MMC is employed into the SST due to its salient features. For design and control of the MMC-based SST, its operational principles are comprehensively analyzed. Based on the analysis, its mathematical model is developed for evaluating steady-state performances. For optimal design of the MMC-based SST, the mathematical model is modified by considering circuit parameters.

One of the challenges of the MMC-based SST is the balancing of capacitor voltages. The performances of various voltage balancing algorithms and different modulation methods have not been comprehensively evaluated. In this thesis, the performances of different voltage-balancing algorithms and modulation methods are analyzed and evaluated. Based on the analysis, two improved voltage-balancing algorithms are proposed in this thesis.

For design of the MMC-based SST, existing references only focus on optimal design of medium-frequency transformer (MFT). In this thesis, an optimal design procedure is developed for the MMC under medium-frequency operation based on the mathematical model of the MMC-based SST. The design performance of MMC is comprehensively evaluated based on free system parameters.
ContributorsZhang, Lei (Author) / Qin, Jiangchao (Thesis advisor) / Ayyanar, Raja (Committee member) / Weng, Yang (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2020
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Description

Conformal deposition of platinum as ultrathin shells on facet-controlled palladium nanocrystals offers a great opportunity to enhance the catalytic performance while reducing its loading. Here we report such a system based on palladium icosahedra. Owing to lateral confinement imposed by twin boundaries and thus vertical relaxation only, the platinum overlayers

Conformal deposition of platinum as ultrathin shells on facet-controlled palladium nanocrystals offers a great opportunity to enhance the catalytic performance while reducing its loading. Here we report such a system based on palladium icosahedra. Owing to lateral confinement imposed by twin boundaries and thus vertical relaxation only, the platinum overlayers evolve into a corrugated structure under compressive strain. For the core-shell nanocrystals with an average of 2.7 platinum overlayers, their specific and platinum mass activities towards oxygen reduction are enhanced by eight- and sevenfold, respectively, relative to a commercial catalyst. Density functional theory calculations indicate that the enhancement can be attributed to the weakened binding of hydroxyl to the compressed platinum surface supported on palladium. After 10,000 testing cycles, the mass activity of the core-shell nanocrystals is still four times higher than the commercial catalyst. These results demonstrate an effective approach to the development of electrocatalysts with greatly enhanced activity and durability.

ContributorsWang, Xue (Author) / Choi, Sang-Il (Author) / Roling, Luke T. (Author) / Luo, Ming (Author) / Ma, Cheng (Author) / Zhang, Lei (Author) / Chi, Miaofang (Author) / Liu, Jingyue (Author) / Xie, Zhaoxiong (Author) / Herron, Jeffrey A. (Author) / Mavrikakis, Manos (Author) / Xia, Younan (Author) / College of Liberal Arts and Sciences (Contributor)
Created2015-07-01
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Description

The unicellular microalga Haematococcus pluvialis has emerged as a promising biomass feedstock for the ketocarotenoid astaxanthin and neutral lipid triacylglycerol. Motile flagellates, resting palmella cells, and cysts are the major life cycle stages of H. pluvialis. Fast-growing motile cells are usually used to induce astaxanthin and triacylglycerol biosynthesis under stress

The unicellular microalga Haematococcus pluvialis has emerged as a promising biomass feedstock for the ketocarotenoid astaxanthin and neutral lipid triacylglycerol. Motile flagellates, resting palmella cells, and cysts are the major life cycle stages of H. pluvialis. Fast-growing motile cells are usually used to induce astaxanthin and triacylglycerol biosynthesis under stress conditions (high light or nutrient starvation); however, productivity of biomass and bioproducts are compromised due to the susceptibility of motile cells to stress. This study revealed that the Photosystem II (PSII) reaction center D1 protein, the manganese-stabilizing protein PsbO, and several major membrane glycerolipids (particularly for chloroplast membrane lipids monogalactosyldiacylglycerol and phosphatidylglycerol), decreased dramatically in motile cells under high light (HL). In contrast, palmella cells, which are transformed from motile cells after an extended period of time under favorable growth conditions, have developed multiple protective mechanisms - including reduction in chloroplast membrane lipids content, downplay of linear photosynthetic electron transport, and activating nonphotochemical quenching mechanisms - while accumulating triacylglycerol. Consequently, the membrane lipids and PSII proteins (D1 and PsbO) remained relatively stable in palmella cells subjected to HL. Introducing palmella instead of motile cells to stress conditions may greatly increase astaxanthin and lipid production in H. pluvialis culture.

ContributorsWang, Baobei (Author) / Zhang, Zhen (Author) / Hu, Qiang (Author) / Sommerfeld, Milton (Author) / Lu, Yinghua (Author) / Han, Danxiang (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-09-15
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Description

The unicellular green microalga Desmodesmus sp. S1 can produce more than 50% total lipid of cell dry weight under high light and nitrogen-limitation conditions. After irradiation by heavy 12C6+ ion beam of 10, 30, 60, 90 or 120 Gy, followed by screening of resulting mutants on 24-well microplates, more than

The unicellular green microalga Desmodesmus sp. S1 can produce more than 50% total lipid of cell dry weight under high light and nitrogen-limitation conditions. After irradiation by heavy 12C6+ ion beam of 10, 30, 60, 90 or 120 Gy, followed by screening of resulting mutants on 24-well microplates, more than 500 mutants were obtained. One of those, named D90G-19, exhibited lipid productivity of 0.298 g L-1⋅d-1, 20.6% higher than wild type, likely owing to an improved maximum quantum efficiency (Fv/Fm) of photosynthesis under stress. This work demonstrated that heavy-ion irradiation combined with high-throughput screening is an effective means for trait improvement. The resulting mutant D90G-19 may be used for enhanced lipid production.

ContributorsHu, Guangrong (Author) / Fan, Yong (Author) / Zhang, Lei (Author) / Yuan, Cheng (Author) / Wang, Jufang (Author) / Hu, Qiang (Author) / Li, Fuli (Author) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2013-04-09
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Description

The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land

The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992–2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface Water Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS’ FW compares favorably (R2 = 91%–94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS’ inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations.

ContributorsSchroeder, Ronny (Author) / McDonald, Kyle C. (Author) / Chapman, Bruce D. (Author) / Jensen, Katherine (Author) / Podest, Erika (Author) / Tessler, Zachary D. (Author) / Bohn, Theodore (Author) / Zimmermann, Reiner (Author) / College of Liberal Arts and Sciences (Contributor)
Created2015-12-09
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Description

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP)

A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate model simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data.

The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m-2 yr-2, equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength.

The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.

ContributorsRawlins, M. A. (Author) / McGuire, A. D. (Author) / Kimball, J. S. (Author) / Dass, P. (Author) / Lawrence, D. (Author) / Burke, E. (Author) / Chen, X. (Author) / Delire, C. (Author) / Koven, C. (Author) / MacDougall, A. (Author) / Peng, S. (Author) / Rinke, A. (Author) / Saito, K. (Author) / Zhang, W. (Author) / Alkama, R. (Author) / Bohn, Theodore (Author) / Ciais, P. (Author) / Decharme, B. (Author) / Gouttevin, I. (Author) / Hajima, T. (Author) / Ji, D. (Author) / Krinner, G. (Author) / Lettenmaier, D. P. (Author) / Miller, P. (Author) / Moore, J. C. (Author) / Smith, B. (Author) / Sueyoshi, T. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2015-07-28
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Description

Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of Ts determines the active-layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts not only drives permafrost thaw/retreat but can also trigger and

Soil temperature (Ts) change is a key indicator of the dynamics of permafrost. On seasonal and interannual timescales, the variability of Ts determines the active-layer depth, which regulates hydrological soil properties and biogeochemical processes. On the multi-decadal scale, increasing Ts not only drives permafrost thaw/retreat but can also trigger and accelerate the decomposition of soil organic carbon. The magnitude of permafrost carbon feedbacks is thus closely linked to the rate of change of soil thermal regimes. In this study, we used nine process-based ecosystem models with permafrost processes, all forced by different observation-based climate forcing during the period 1960–2000, to characterize the warming rate of Ts in permafrost regions. There is a large spread of Ts trends at 20 cm depth across the models, with trend values ranging from 0.010 ± 0.003 to 0.031 ± 0.005 °C yr-1. Most models show smaller increase in Ts with increasing depth. Air temperature (Tsub>a) and longwave downward radiation (LWDR) are the main drivers of Ts trends, but their relative contributions differ amongst the models. Different trends of LWDR used in the forcing of models can explain 61 % of their differences in Ts trends, while trends of Ta only explain 5 % of the differences in Ts trends. Uncertain climate forcing contributes a larger uncertainty in Ts trends (0.021 ± 0.008 °C yr-1, mean ± standard deviation) than the uncertainty of model structure (0.012 ± 0.001 °C yr-1), diagnosed from the range of response between different models, normalized to the same forcing. In addition, the loss rate of near-surface permafrost area, defined as total area where the maximum seasonal active-layer thickness (ALT) is less than 3 m loss rate, is found to be significantly correlated with the magnitude of the trends of Ts at 1 m depth across the models (R = −0.85, P = 0.003), but not with the initial total near-surface permafrost area (R = −0.30, P = 0.438). The sensitivity of the total boreal near-surface permafrost area to Ts at 1 m is estimated to be of −2.80 ± 0.67 million km2°C-1. Finally, by using two long-term LWDR data sets and relationships between trends of LWDR and Ts across models, we infer an observation-constrained total boreal near-surface permafrost area decrease comprising between 39 ± 14  ×  103 and 75 ± 14  ×  103km2yr-1 from 1960 to 2000. This corresponds to 9–18 % degradation of the current permafrost area.

ContributorsPeng, S. (Author) / Ciais, P. (Author) / Krinner, G. (Author) / Wang, T. (Author) / Gouttevin, I. (Author) / McGuire, A. D. (Author) / Lawrence, D. (Author) / Burke, E. (Author) / Chen, X. (Author) / Decharme, B. (Author) / Koven, C. (Author) / MacDougall, A. (Author) / Rinke, A. (Author) / Saito, K. (Author) / Zhang, W. (Author) / Alkama, R. (Author) / Bohn, Theodore (Author) / Delire, C. (Author) / Hajima, T. (Author) / Ji, D. (Author) / Lettenmaier, D. P. (Author) / Miller, P. A. (Author) / Moore, J. C. (Author) / Smith, B. (Author) / Sueyoshi, T. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-01-20