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In this thesis, applications of sparsity, specifically sparse-tensors are motivated in physics.An algorithm is introduced to natively compute sparse-tensor's partial-traces, along with direct implementations in popular python libraries for immediate use. These applications include the infamous exponentially-scaling (with system size) Quantum-Many-Body problems (both Heisenberg/spin-chain-like and Chemical Hamiltonian models). This sparsity

In this thesis, applications of sparsity, specifically sparse-tensors are motivated in physics.An algorithm is introduced to natively compute sparse-tensor's partial-traces, along with direct implementations in popular python libraries for immediate use. These applications include the infamous exponentially-scaling (with system size) Quantum-Many-Body problems (both Heisenberg/spin-chain-like and Chemical Hamiltonian models). This sparsity aspect is stressed as an important and essential feature in solving many real-world physical problems approximately-and-numerically. These include the original motivation of solving radiation-damage questions for ultrafast light and electron sources.
ContributorsCandanedo, Julio (Author) / Beckstein, Oliver (Thesis advisor) / Arenz, Christian (Thesis advisor) / Keeler, Cynthia (Committee member) / Erten, Onur (Committee member) / Arizona State University (Publisher)
Created2023
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This thesis is developed in the context of biomanufacturing of modern products that have the following properties: require short design to manufacturing time, they have high variability due to a high desired level of patient personalization, and, as a result, may be manufactured in low volumes. This area at the

This thesis is developed in the context of biomanufacturing of modern products that have the following properties: require short design to manufacturing time, they have high variability due to a high desired level of patient personalization, and, as a result, may be manufactured in low volumes. This area at the intersection of therapeutics and biomanufacturing has become increasingly important: (i) a huge push toward the design of new RNA nanoparticles has revolutionized the science of vaccines due to the COVID-19 pandemic; (ii) while the technology to produce personalized cancer medications is available, efficient design and operation of manufacturing systems is not yet agreed upon. In this work, the focus is on operations research methodologies that can support faster design of novel products, specifically RNA; and methods for the enabling of personalization in biomanufacturing, and will specifically look at the problem of cancer therapy manufacturing. Across both areas, methods are presented attempting to embed pre-existing knowledge (e.g., constraints characterizing good molecules, comparison between structures) as well as learn problem structure (e.g., the landscape of the rewards function while synthesizing the control for a single use bioreactor). This thesis produced three key outcomes: (i) ExpertRNA for the prediction of the structure of an RNA molecule given a sequence. RNA structure is fundamental in determining its function. Therefore, having efficient tools for such prediction can make all the difference for a scientist trying to understand optimal molecule configuration. For the first time, the algorithm allows expert evaluation in the loop to judge the partial predictions that the tool produces; (ii) BioMAN, a discrete event simulation tool for the study of single-use biomanufacturing of personalized cancer therapies. The discrete event simulation engine was designed tailored to handle the efficient scheduling of many parallel events which is cause by the presence of single use resources. This is the first simulator of this type for individual therapies; (iii) Part-MCTS, a novel sequential decision-making algorithm to support the control of single use systems. This tool integrates for the first-time simulation, monte-carlo tree search and optimal computing budget allocation for managing the computational effort.
ContributorsLiu, Menghan (Author) / Pedrielli, Giulia (Thesis advisor) / Bertsekas, Dimitri (Committee member) / Pan, Rong (Committee member) / Sulc, Petr (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2023
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A key contribution of human factors engineering is the concept of workload: a construct that represents the relationship between an operator’s cognitive resources, the demands of their task, and performance. Understanding workload can lead to improvements in safety and performance for people working in critical environments, particularly within action teams.

A key contribution of human factors engineering is the concept of workload: a construct that represents the relationship between an operator’s cognitive resources, the demands of their task, and performance. Understanding workload can lead to improvements in safety and performance for people working in critical environments, particularly within action teams. Recently, there has been interest in considering how the workload of a team as a whole may differ from that of an individual, prompting investigation into team workload as a distinct team-level construct. In empirical research, team-level workload is often considered as the sum or average of individual team members' workloads. However, the intrinsic characteristics of action teams—such as interdependence and heterogeneity—challenge this assumption, and traditional methods of measuring team workload might be unsuitable. This dissertation delves into this issue with a review of empirical work in action teams, pinpointing several gaps. Next, the development of a testbed is described and used to address two pressing gaps regarding the impact of interdependence and how team communications relate to team workload states and performance. An experiment was conducted with forty 3-person teams collaborating in an action team task. Results of this experiment suggest that the traditional way of measuring workload in action teams via subjective questionnaires averaged at the team level has some major shortcomings, particularly when demands are elevated, and action teams are highly interdependent. The results also suggested that several communication measures are associated with increases in demands, laying the groundwork for team-level communication-based measures of team workload. The results are synthesized with findings from the literature to provide a way forward for conceptualizing and measuring team workload in action teams.
ContributorsJohnson, Craig Jonathon (Author) / Cooke, Nancy J (Thesis advisor) / Gutzwiller, Robert S (Committee member) / Holder, Eric (Committee member) / Amazeen, Polemnia G (Committee member) / Arizona State University (Publisher)
Created2023
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Description
In this dissertation, the nanofabrication process is characterized for fabrication of nanostructure on surface of silicon and gallium phosphide using silica nanosphere lithography (SNL) and metal assisted chemical etching (MACE) process. The SNL process allows fast process time and well defined silica nanosphere monolayer by spin-coating process after mixing N,N-dimethyl-formamide

In this dissertation, the nanofabrication process is characterized for fabrication of nanostructure on surface of silicon and gallium phosphide using silica nanosphere lithography (SNL) and metal assisted chemical etching (MACE) process. The SNL process allows fast process time and well defined silica nanosphere monolayer by spin-coating process after mixing N,N-dimethyl-formamide (DMF) solvent. The MACE process achieves the high aspect ratio structure fabrication using the reaction between metal and wet chemical. The nanostructures are fabricated on Si surface for enhanced light management, but, without proper surface passivation those gains hardly impact the performance of the solar cell. The surface passivation of nanostructures is challenging, not only due to larger surface areas and aspect ratios, but also has a direct result of the nanofabrication processes. In this research, the surface passivation of silicon nanostructures is improved by modifying the silica nanosphere lithography (SNL) and the metal assisted chemical etching (MACE) processes, frequently used to fabricate nanostructures. The implementation of a protective silicon oxide layer is proposed prior to the lithography process to mitigate the impact of the plasma etching during the SNL. Additionally, several adhesion layers are studied, chromium (Cr), nickel (Ni) and titanium (Ti) with gold (Au), used in the MACE process. The metal contamination is one of main damage and Ti makes the mitigation of metal contamination. Finally, a new chemical etching step is introduced, using potassium hydroxide at room temperature, to smooth the surface of the nanostructures after the MACE process. This chemical treatment allows to improve passivation by surface area control and removing surface defects. In this research, I demonstrate the Aluminum Oxide (Al2O3) passivation on nanostructure using atomic layer deposition (ALD) process. 10nm of Al2O3 layer makes effective passivation on nanostructure with optimized post annealing in forming gas (N2/H2) environment. However, 10nm thickness is not suitable for hetero structure because of carrier transportation. For carrier transportation, ultrathin Al2O3 (≤ 1nm) layer is used for passivation, but effective passivation is not achieved because of insufficient hydrogen contents. This issue is solved to use additional ultrathin SiO2 (1nm) below Al2O3 layer and hydrogenation from doped a-Si:H. Moreover, the nanostructure is creased on gallium phosphide (GaP) by SNL and MACE process. The fabrication process is modified by control of metal layer and MACE solution.
ContributorsKim, Sangpyeong (Author) / Honsberg, Christiana (Thesis advisor) / Bowden, Stuart (Committee member) / Goryll, Michael (Committee member) / Augusto, Andre (Committee member) / Arizona State University (Publisher)
Created2021
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Late first row transitional metals have attracted attention for the development of sustainable catalysts due to their low cost and natural abundance. This dissertation discusses the utilization of redox-active ligands to overcome one electron redox processes exhibited by these base metals. Previous advances in carbonyl and carboxylate hydrosilylation using redox

Late first row transitional metals have attracted attention for the development of sustainable catalysts due to their low cost and natural abundance. This dissertation discusses the utilization of redox-active ligands to overcome one electron redox processes exhibited by these base metals. Previous advances in carbonyl and carboxylate hydrosilylation using redox active ligand-supported complexes such as (Ph2PPrPDI)Mn and (Ph2PPrDI)Ni have been reviewed in this thesis to set the stage for the experimental work described herein.The synthesis and electronic structure of late first row transition metal complexes featuring the Ph2PPrPDI chelate was pursued. Utilizing these complexes as catalysts for a variety of reactions gave a recurring trend in catalytic activity. DFT calculations suggest that the trend in activity observed for these complexes is associated with the ease of phosphine arm dissociation. Furthermore, the synthesis and characterization of a phosphine-substituted aryl diimine ligand, Ph2PPrADI-H was explored. Addition of Ph2PPrADI-H to CoCl2 resulted in C-H activation of the ligand backbone and formation of [(Ph2PPrADI)CoCl][Co2Cl6]0.5. Reduction of [(Ph2PPrADI)CoCl][Co2Cl6]0.5 afforded the precatalyst, (Ph2PPrADI)Co, that was found to effectively catalyze carbonyl hydrosilylation. At low catalyst loading, TOFs of up to 330 s-1 could be achieved, the highest ever reported for metal-catalyzed carbonyl hydrosilylation. This dissertation also reports the first cobalt catalyzed pathway for dehydrocoupling diamines or polyamines with polymethylhydrosiloxanes to form crosslinked copolymers. At low catalyst loading, (Ph2PPrADI)Co was found to catalyze the dehydrocoupling of 1,3-diaminopropane and TMS-terminated PMHS with TOFs of up to 157 s-1, the highest TOF ever reported for a Si-N dehydrocoupling reaction. Dehydrocoupling of diamines with hydride-terminated polydimethylsiloxane yielded linear diamine siloxane copolymers as oils. Finally, dehydrocoupling between diamines and organosilanes catalyzed by a manganese dimer complex, [(2,6-iPr2PhBDI)Mn(μ-H)]2, has allowed for the preparation of silane diamine copolymers. Exceptional solvent absorption capacity was demonstrated by the solid networks, which were found to absorb up to 7 times their own weight. Furthermore, degradation of these networks revealed that their Si-N backbones are easily hydrolysable when exposed to air. The use of lightly crosslinked copolymers as coatings was also studied using SEM analysis.
ContributorsSharma, Anuja (Author) / Trovitch, Ryan J. (Thesis advisor) / Seo, Dong-Kyun (Committee member) / Moore, Gary F. (Committee member) / Arizona State University (Publisher)
Created2024
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Description
Microplastics, plastics smaller than 5 mm, are an emerging concern worldwide due to their potential adverse effects on the environment and human health. Microplastics have the potential to biomagnify through the food chain, and are prone to adsorbing organic pollutants and heavy metals. Therefore, there is an urgent need to

Microplastics, plastics smaller than 5 mm, are an emerging concern worldwide due to their potential adverse effects on the environment and human health. Microplastics have the potential to biomagnify through the food chain, and are prone to adsorbing organic pollutants and heavy metals. Therefore, there is an urgent need to assess the extent of microplastic contamination in different environments. The occurrence of microplastics in the atmosphere of Tempe, AZ was investigated and results show concentrations as high as 1.1 microplastics/m3. The most abundant identified polymer was polyvinyl chloride. However, chemical characterization is fraught with challenges, with a majority of microplastics remaining chemically unidentified. Laboratory experiments simulating weathering of microplastics revealed that Raman spectra of microplastics change over time due to weathering processes. This work also studied the spatial variation of microplastics in soil in Phoenix and the surrounding areas of the Sonoran Desert, and microplastic abundances ranged from 122 to 1299 microplastics/kg with no clear trends between different locations, and substantial total deposition of microplastics occurring in the same location with resuspension and redistribution of deposited microplastics likely contributing to unclear spatial trends. Temporal variation of soil microplastics from 2005 to 2015 show a systematic increase in the abundance of microplastics. Polyethylene was prominent in all soil samples. Further, recreational surface waters were investigated as a potential source of microplastics in aquatic environments. The temporal variation of microplastics in the Salt River, AZ over the course of one day depicted an increase of 8 times in microplastic concentration at peak activity time of 16:00 hr compared to 8:00 hr. Concurrently, microplastic concentrations in surface water samples from apartment community swimming pools in Tempe, AZ depicted substantial variability with concentrations as high as 254,574 MPs/m3. Polyester and Polyamide fibers were prevalent in surface water samples, indicating a release from synthetic fabrics. Finally, a method for distinguishing tire wear microplastics from soot in ambient aerosol samples was developed using Programmed Thermal Analysis, that allows for the quantification of Elemental Carbon. The method was successfully applied on urban aerosol samples with results depicting substantial fractions of tire wear in urban atmospheric environments.
ContributorsChandrakanthan, Kanchana (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2024