Matching Items (1,289)
Filtering by
- All Subjects: Materials Science
- All Subjects: Mechanical Engineering
- All Subjects: Biomedical Engineering
- Member of: Theses and Dissertations
Description
An ongoing effort in the photovoltaic (PV) industry is to reduce the major manufacturing cost components of solar cells, the great majority of which are based on crystalline silicon (c-Si). This includes the substitution of screenprinted silver (Ag) cell contacts with alternative copper (Cu)-based contacts, usually applied with plating. Plated Cu contact schemes have been under study for many years with only minor traction in industrial production. One of the more commonly-cited barriers to the adoption of Cu-based contacts for photovoltaics is long-term reliability, as Cu is a significant contaminant in c-Si, forming precipitates that degrade performance via degradation of diode character and reduction of minority carrier lifetime. Cu contamination from contacts might cause degradation during field deployment if Cu is able to ingress into c-Si. Furthermore, Cu contamination is also known to cause a form of light-induced degradation (LID) which further degrades carrier lifetime when cells are exposed to light.
Prior literature on Cu-contact reliability tended to focus on accelerated testing at the cell and wafer level that may not be entirely replicative of real-world environmental stresses in PV modules. This thesis is aimed at advancing the understanding of Cu-contact reliability from the perspective of quasi-commercial modules under more realistic stresses. In this thesis, c-Si solar cells with Cu-plated contacts are fabricated, made into PV modules, and subjected to environmental stress in an attempt to induce hypothesized failure modes and understand any new vulnerabilities that Cu contacts might introduce. In particular, damp heat stress is applied to conventional, p-type c-Si modules and high efficiency, n-type c-Si heterojunction modules. I present evidence of Cu-induced diode degradation that also depends on PV module materials, as well as degradation unrelated to Cu, and in either case suggest engineering solutions to the observed degradation. In a forensic search for degradation mechanisms, I present novel evidence of Cu outdiffusion from contact layers and encapsulant-driven contact corrosion as potential key factors. Finally, outdoor exposures to light uncover peculiarities in Cu-plated samples, but do not point to especially serious vulnerabilities.
Prior literature on Cu-contact reliability tended to focus on accelerated testing at the cell and wafer level that may not be entirely replicative of real-world environmental stresses in PV modules. This thesis is aimed at advancing the understanding of Cu-contact reliability from the perspective of quasi-commercial modules under more realistic stresses. In this thesis, c-Si solar cells with Cu-plated contacts are fabricated, made into PV modules, and subjected to environmental stress in an attempt to induce hypothesized failure modes and understand any new vulnerabilities that Cu contacts might introduce. In particular, damp heat stress is applied to conventional, p-type c-Si modules and high efficiency, n-type c-Si heterojunction modules. I present evidence of Cu-induced diode degradation that also depends on PV module materials, as well as degradation unrelated to Cu, and in either case suggest engineering solutions to the observed degradation. In a forensic search for degradation mechanisms, I present novel evidence of Cu outdiffusion from contact layers and encapsulant-driven contact corrosion as potential key factors. Finally, outdoor exposures to light uncover peculiarities in Cu-plated samples, but do not point to especially serious vulnerabilities.
ContributorsKaras, Joseph (Author) / Bowden, Stuart (Thesis advisor) / Alford, Terry (Thesis advisor) / Tamizhmani, Govindasamy (Committee member) / Michaelson, Lynne (Committee member) / Arizona State University (Publisher)
Created2020
Description
Information exists in various forms and a better utilization of the available information can benefit the system awareness and response predictions. The focus of this dissertation is on the fusion of different types of information using Bayesian-Entropy method. The Maximum Entropy method in information theory introduces a unique way of handling information in the form of constraints. The Bayesian-Entropy (BE) principle is proposed to integrate the Bayes’ theorem and Maximum Entropy method to encode extra information. The posterior distribution in Bayesian-Entropy method has a Bayesian part to handle point observation data, and an Entropy part that encodes constraints, such as statistical moment information, range information and general function between variables. The proposed method is then extended to its network format as Bayesian Entropy Network (BEN), which serves as a generalized information fusion tool for diagnostics, prognostics, and surrogate modeling.
The proposed BEN is demonstrated and validated with extensive engineering applications. The BEN method is first demonstrated for diagnostics of gas pipelines and metal/composite plates for damage diagnostics. Both empirical knowledge and physics model are integrated with direct observations to improve the accuracy for diagnostics and to reduce the training samples. Next, the BEN is demonstrated in prognostics and safety assessment in air traffic management system. Various information types, such as human concepts, variable correlation functions, physical constraints, and tendency data, are fused in BEN to enhance the safety assessment and risk prediction in the National Airspace System (NAS). Following this, the BE principle is applied in surrogate modeling. Multiple algorithms are proposed based on different type of information encoding, such as Bayesian-Entropy Linear Regression (BELR), Bayesian-Entropy Semiparametric Gaussian Process (BESGP), and Bayesian-Entropy Gaussian Process (BEGP) are demonstrated with numerical toy problems and practical engineering analysis. The results show that the major benefits are the superior prediction/extrapolation performance and significant reduction of training samples by using additional physics/knowledge as constraints. The proposed BEN offers a systematic and rigorous way to incorporate various information sources. Several major conclusions are drawn based on the proposed study.
The proposed BEN is demonstrated and validated with extensive engineering applications. The BEN method is first demonstrated for diagnostics of gas pipelines and metal/composite plates for damage diagnostics. Both empirical knowledge and physics model are integrated with direct observations to improve the accuracy for diagnostics and to reduce the training samples. Next, the BEN is demonstrated in prognostics and safety assessment in air traffic management system. Various information types, such as human concepts, variable correlation functions, physical constraints, and tendency data, are fused in BEN to enhance the safety assessment and risk prediction in the National Airspace System (NAS). Following this, the BE principle is applied in surrogate modeling. Multiple algorithms are proposed based on different type of information encoding, such as Bayesian-Entropy Linear Regression (BELR), Bayesian-Entropy Semiparametric Gaussian Process (BESGP), and Bayesian-Entropy Gaussian Process (BEGP) are demonstrated with numerical toy problems and practical engineering analysis. The results show that the major benefits are the superior prediction/extrapolation performance and significant reduction of training samples by using additional physics/knowledge as constraints. The proposed BEN offers a systematic and rigorous way to incorporate various information sources. Several major conclusions are drawn based on the proposed study.
ContributorsWang, Yuhao (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Mignolet, Marc (Committee member) / Yan, Hao (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2020
Description
There are increasing demands for gas sensors in air quality and human health monitoring applications. The qualifying sensor technology must be highly sensitive towards ppb level gases of interest, such as acetylene (C2H2), hydrogen sulfide (H2S), and volatile organic compounds. Among the commercially available sensor technologies, conductometric gas sensors with nanoparticles of oxide semiconductors as sensing materials hold significant advantages in cost, size, and cross-compatibility. However, semiconductor gas sensors must overcome some major challenges in thermal stability, sensitivity, humidity interference, and selectivity before potential widespread adoption in air quality and human health monitoring applications.
The focus of this dissertation is to tackle these issues by optimizing the composition and the morphology of the nanoparticles, and by innovating the structure of the sensing film assembled with the nanoparticles. From the nanoparticles perspective, the thermal stability of tin oxide nanoparticles with different Al dopant concentrations was studied, and the results indicate that within certain range of doping concentration, the dopants segregated at the grain surface can improve the thermal stability by stabilizing the grain boundaries.
From the sensing film perspective, a novel self-assembly approach was developed for copper oxide nanosheets and the sensor response towards H2S gas was revealed to decrease monotonically by more than 60% as the number of layers increase from 1 to 300 (thickness: 0.03-10 μm). Moreover, a sensing mechanism study on the humidity influence on H2S detection was performed to gain more understandings of the role of the hydroxyl group in the surface reaction, and humidity independent response was observed in the monolayer film at 325 ℃. With a more precise deposition tool (Langmuir-Blodgett trough), monolayer film of zinc oxide nanowires sensitized with gold catalyst was prepared, and highly sensitive and specific response to C2H2 in the ppb range was observed. Furthermore, the effect of surface topography of the monolayer film on stabilizing noble metal catalyst, and the sensitization mechanism of gold were investigated.
Lastly, a semiconductor sensor array was developed to analyze the composition of gases dissolved in transformer oil to demonstrate the industrial application of this sensor technology.
The focus of this dissertation is to tackle these issues by optimizing the composition and the morphology of the nanoparticles, and by innovating the structure of the sensing film assembled with the nanoparticles. From the nanoparticles perspective, the thermal stability of tin oxide nanoparticles with different Al dopant concentrations was studied, and the results indicate that within certain range of doping concentration, the dopants segregated at the grain surface can improve the thermal stability by stabilizing the grain boundaries.
From the sensing film perspective, a novel self-assembly approach was developed for copper oxide nanosheets and the sensor response towards H2S gas was revealed to decrease monotonically by more than 60% as the number of layers increase from 1 to 300 (thickness: 0.03-10 μm). Moreover, a sensing mechanism study on the humidity influence on H2S detection was performed to gain more understandings of the role of the hydroxyl group in the surface reaction, and humidity independent response was observed in the monolayer film at 325 ℃. With a more precise deposition tool (Langmuir-Blodgett trough), monolayer film of zinc oxide nanowires sensitized with gold catalyst was prepared, and highly sensitive and specific response to C2H2 in the ppb range was observed. Furthermore, the effect of surface topography of the monolayer film on stabilizing noble metal catalyst, and the sensitization mechanism of gold were investigated.
Lastly, a semiconductor sensor array was developed to analyze the composition of gases dissolved in transformer oil to demonstrate the industrial application of this sensor technology.
ContributorsMiao, Jiansong (Author) / Lin, Jerry Y.S. (Thesis advisor) / Forzani, Erica (Committee member) / Liu, Jingyue (Committee member) / Li, Jian (Committee member) / Arizona State University (Publisher)
Created2020
Description
Perovskite solar cells are the next generation organic-inorganic hybrid technology and have achieved remarkable efficiencies comparable to Si-based conventional solar cells. Since their inception in 2009 with an efficiency of 3.9%, they have improved tremendously over the past decade and recently demonstrated 25.2% efficiency for single-junction devices. There are a few hurdles, however, that prevent this technology from realizing their full potential, such as stability and toxicity of the perovskites. Apart from solution processing in the fabrication of perovskites, precursor composition plays a major role in determining the quality of the thin film and its general properties. This work studies novel approaches for improving the efficiency and stability of the perovskite solar cells with minimized toxicity. The effect of excess Pb on photo-degradation in MAPbI3 perovskites in an inverted device architecture was studied with a focus on improving stability and efficiency. Precursor concentration with 5% excess Pb was found to be optimal for better efficiency and stability against photo-degradation. Further improvements in efficiency were made possible through the addition of Zirconium Acetylacetonate as a secondary electron buffer layer. A concentration of 1.5mg/ml was found to be optimal for demonstrating better efficiency and stability. Partial substitution of Pb with non-toxic Sr was also studied for improving the stability of inverted devices. Using acetate-derived precursors, 10% Sr was introduced into perovskites for improvements to the stability of the device.
In another study, triple-cation perovskites with FAMACs cations were studied with doping different amounts of Phenyl Ethyl Ammonium (PEA) to induce a quasi 2D-3D structure for improved moisture stability. Doping the perovskite with 1.67% PEA was found to be best for improved morphology with fewer pinholes, which further resulted in better VOC and stability. A passivation effect for triple-cation perovskites was further proposed with the addition of a Guanidinium Iodide layer on the perovskite. Concentrations of 1mg/ml and 2mg/ml were demonstrated to be best for reducing defects and trap states and increasing the overall stability of the device.
In another study, triple-cation perovskites with FAMACs cations were studied with doping different amounts of Phenyl Ethyl Ammonium (PEA) to induce a quasi 2D-3D structure for improved moisture stability. Doping the perovskite with 1.67% PEA was found to be best for improved morphology with fewer pinholes, which further resulted in better VOC and stability. A passivation effect for triple-cation perovskites was further proposed with the addition of a Guanidinium Iodide layer on the perovskite. Concentrations of 1mg/ml and 2mg/ml were demonstrated to be best for reducing defects and trap states and increasing the overall stability of the device.
ContributorsYerramilli, Aditya (Author) / Alford, Terry (Thesis advisor) / Theodore, David (Committee member) / Chen, Yuanqing (Committee member) / Arizona State University (Publisher)
Created2020
Description
Almost all mechanical and electro-mechanical products are assemblies of multiple parts, either because of requirements for relative motion, or use of different materials, shape/size differences. Thus, assembly design is the very crux of engineering design. In addition to nominal design of an assembly, there is also tolerance design to determine allowable manufacturing variations to ensure proper functioning and assemblability. Most of the flexible assemblies are made by stamping sheet metal. Sheet metal stamping process involves plastically deforming sheet metals using dies. Sub-assemblies of two or more components are made with either spot-welding or riveting operations. Various sub-assemblies are finally joined, using spot-welds or rivets, to create the desired assembly. When two components are brought together for assembly, they do not align exactly; this causes gaps and irregularities in assemblies. As multiple parts are stacked, errors accumulate further. Stamping leads to variable deformations due to residual stresses and elastic recovery from plastic strain of metals; this is called as the ‘spring-back’ effect. When multiple components are stacked or assembled using spot welds, input parameters variations, such as sheet metal thickness, number and order of spot welds, cause variations in the exact shape of the final assembly in its free state. It is essential to understand the influence of these input parameters on the geometric variations of both the individual components and the assembly created using these components. Design of Experiment is used to generate principal effect study which evaluates the influence of input parameters on output parameters. The scope of this study is to quantify the geometric variations for a flexible assembly and evaluate their dependence on specific input variables. The 3 input variables considered are the thickness of the sheet material, the number of spot welds used and the spot-welding order to create the assembly. To quantify the geometric variations, sprung-back nodal points along lines, circular arcs, a combination of these, and a specific profile are reduced to metrologically simulated features.
ContributorsJoshi, Abhishek (Author) / Ren, Yi (Thesis advisor) / Davidson, Joseph (Committee member) / Shah, Jami (Committee member) / Arizona State University (Publisher)
Created2020
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
The ability to inhibit a planned but inappropriate response, and switch to executing a goal-relevant motor response, is critically important for the regulation of motor behaviors. Inhibition and switching could be mediated by various control mechanisms. Proactive control uses contextual information (cues) to plan the response for the target stimulus (probe) based on the expectation of a response inhibition or switching stimulus combination. Previous work has reported the involvement of several brain areas associated with proactive inhibition and switching, e.g., dorsolateral prefrontal cortex, anterior cingulate cortex, inferior frontal junction, and pre-supplementary motor area. However, how these areas interact and their functional role in different types of cognitive control is still debated. An AX-version of the continuous performance task (AX-CPT) was used to examine proactive inhibition and switching of motor actions. In a typical AX-CPT trial, a contextual cue stimulus is presented, followed by a probe stimulus after a specific inter-stimulus interval. As part of a trial sequence, if a target cue and target probe are presented, a target response is to be provided when the probe is observed. Otherwise, a non-target response is to be provided for all other stimuli. A behavioral switching AX-CPT experiment (48 subjects) was conducted to explore the parameters that induce a proactive shift in the motor response. Participants who performed the AX-CPT task with relatively shorter interstimulus interval predominantly and consistently exhibited proactive control behavior. A follow-up pilot study (3 subjects) of response inhibition versus response switching AX-CPT was performed using 256-channel high-density electroencephalography (HD-EEG). HD-EEG was used to identify the time course of cortical activation in brain areas associated with response inhibition. It was observed that one out of three participants used a proactive strategy for response switching based on probe response error and probe response reaction time. Instantaneous amplitude spatial maps obtained from HD-EEG revealed cortical activity corresponding to conflict between proactively-prepared incorrect responses and reactively-corrected goal-relevant responses after the probe was presented.
ContributorsMysore, Archana Shashidhar (Author) / Santello, Marco (Thesis advisor) / Blais, Christopher (Committee member) / Brewer, Gene (Committee member) / Tillery, Stephen Helms (Committee member) / Arizona State University (Publisher)
Created2020
Description
Thermal Energy Storage (TES) is of great significance for many engineering applications as it allows surplus thermal energy to be stored and reused later, bridging the gap between requirement and energy use. Phase change materials (PCMs) are latent heat-based TES which have the ability to store and release heat through phase transition processes over a relatively narrow temperature range. PCMs have a wide range of operating temperatures and therefore can be used in various applications such as stand-alone heat storage in a renewable energy system, thermal storage in buildings, water heating systems, etc. In this dissertation, various PCMs are incorporated and investigated numerically and experimentally with different applications namely a thermochemical metal hydride (MH) storage system and thermal storage in buildings. In the second chapter, a new design consisting of an MH reactor encircled by a cylindrical sandwich bed packed with PCM is proposed. The role of the PCM is to store the heat released by the MH reactor during the hydrogenation process and reuse it later in the subsequent dehydrogenation process. In such a system, the exothermic and endothermic processes of the MH reactor can be utilized effectively by enhancing the thermal exchange between the MH reactor and the PCM bed. Similarly, in the third chapter, a novel design that integrates the MH reactor with cascaded PCM beds is proposed. In this design, two different types of PCMs with different melting temperatures and enthalpies are arranged in series to improve the heat transfer rate and consequently shorten the time duration of the hydrogenation and dehydrogenation processes. The performance of the new designs (in chapters 2 and 3) is investigated numerically and compared with the conventional designs in the literature. The results indicate that the new designs can significantly enhance the time duration of MH reaction (up to 87%). In the fourth chapter, organic coconut oil PCM (co-oil PCM) is explored experimentally and numerically for the first time as a thermal management tool in building applications. The results show that co-oil PCM can be a promising solution to improve the indoor thermal environment in semi-arid regions.
ContributorsAlqahtani, Talal (Author) / Phelan, Patrick E (Thesis advisor) / Shuaib, Abdelrahman (Committee member) / Mellouli, Sofiene (Committee member) / Wang, Robert (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2020
Description
Extracellular vesicles (EVs) are membranous particles that are abundantly secreted in the circulation system by most cells and can be found in most biological fluids. Among different EV subtypes, exosomes are small particles (30 – 150 nm) that are generated through the double invagination of the lipid bilayer membrane of cell. Therefore, they mirror the cell membrane proteins and contain proteins, RNAs, and DNAs that can represent the phenotypic state of their cell of origin, hence considered promising biomarker candidates. Importantly, in most pathological conditions, such as cancer and infection, diseased cells secrete more EVs and the disease associated exosomes have shown great potential to serve as biomarkers for early diagnosis, disease staging, and treatment monitoring. However, using EVs as diagnostic or prognostic tools in the clinic is hindered by the lack of a rapid, sensitive, purification-free technique for their isolation and characterization. Developing standardized assays that can translate the emerging academic EV biomarker discoveries to clinically relevant procedures is a bottleneck that have slowed down advancements in medical research. Integrating widely known immunoassays with plasmonic sensors has shown the promise to detect minute amounts of antigen present in biological sample, based on changes of ambient optical refractive index, and achieve ultra-sensitivity. Plasmonic sensors take advantage of the enhanced interaction of electromagnetic radiations with electron clouds of plasmonic materials at the dielectric-metal interface in tunable wavelengths.
ContributorsAmrollahi, Pouy (Author) / Wang, Xiao (Thesis advisor) / Forzani, Erica (Committee member) / Hu, Tony Ye (Committee member) / Arizona State University (Publisher)
Created2020
Description
Energy return in footwear is associated with the damping behavior of midsole foams, which stems from the combination of cellular structure and polymeric material behavior. Recently, traditional ethyl vinyl acetate (EVA) foams have been replaced by BOOST(TM) foams, thereby reducing the energetic cost of running. These are bead foams made from expanded thermoplastic polyurethane (eTPU), which have a multi-scale structure consisting of fused porous beads, at the meso-scale, and thousands of small closed cells within the beads at the micro-scale. Existing predictive models coarsely describe the macroscopic behavior but do not take into account strain localizations and microstructural heterogeneities. Thus, enhancement in material performance and optimization requires a comprehensive understanding of the foam’s cellular structure at all length scales and its influence on mechanical response.
This dissertation focused on characterization and deformation behavior of eTPU bead foams with a unique graded cell structure at the micro and meso-scale. The evolution of the foam structure during compression was studied using a combination of in situ lab scale and synchrotron x-ray tomography using a four-dimensional (4D, deformation + time) approach. A digital volume correlation (DVC) method was developed to elucidate the role of cell structure on local deformation mechanisms. The overall mechanical response was also studied ex situ to probe the effect of cell size distribution on the force-deflection behavior. The radial variation in porosity and ligament thickness profoundly influenced the global mechanical behavior. The correlation of changes in void size and shape helped in identifying potentially weak regions in the microstructure. Strain maps showed the initiation of failure in cell structure and it was found to be influenced by the heterogeneities around the immediate neighbors in a cluster of voids. Poisson’s ratio evaluated from DVC was related to the microstructure of the bead foams. The 4D approach taken here provided an in depth and mechanistic understanding of the material behavior, both at the bead and plate levels, that will be invaluable in designing the next generation of high-performance footwear.
This dissertation focused on characterization and deformation behavior of eTPU bead foams with a unique graded cell structure at the micro and meso-scale. The evolution of the foam structure during compression was studied using a combination of in situ lab scale and synchrotron x-ray tomography using a four-dimensional (4D, deformation + time) approach. A digital volume correlation (DVC) method was developed to elucidate the role of cell structure on local deformation mechanisms. The overall mechanical response was also studied ex situ to probe the effect of cell size distribution on the force-deflection behavior. The radial variation in porosity and ligament thickness profoundly influenced the global mechanical behavior. The correlation of changes in void size and shape helped in identifying potentially weak regions in the microstructure. Strain maps showed the initiation of failure in cell structure and it was found to be influenced by the heterogeneities around the immediate neighbors in a cluster of voids. Poisson’s ratio evaluated from DVC was related to the microstructure of the bead foams. The 4D approach taken here provided an in depth and mechanistic understanding of the material behavior, both at the bead and plate levels, that will be invaluable in designing the next generation of high-performance footwear.
ContributorsSundaram Singaravelu, Arun Sundar (Author) / Chawla, Nikhilesh (Thesis advisor) / Emady, Heather (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020