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- Genre: Doctoral Dissertation
Description
Although high performance, light-weight composites are increasingly being used in applications ranging from aircraft, rotorcraft, weapon systems and ground vehicles, the assurance of structural reliability remains a critical issue. In composites, damage is absorbed through various fracture processes, including fiber failure, matrix cracking and delamination. An important element in achieving reliable composite systems is a strong capability of assessing and inspecting physical damage of critical structural components. Installation of a robust Structural Health Monitoring (SHM) system would be very valuable in detecting the onset of composite failure. A number of major issues still require serious attention in connection with the research and development aspects of sensor-integrated reliable SHM systems for composite structures. In particular, the sensitivity of currently available sensor systems does not allow detection of micro level damage; this limits the capability of data driven SHM systems. As a fundamental layer in SHM, modeling can provide in-depth information on material and structural behavior for sensing and detection, as well as data for learning algorithms. This dissertation focusses on the development of a multiscale analysis framework, which is used to detect various forms of damage in complex composite structures. A generalized method of cells based micromechanics analysis, as implemented in NASA's MAC/GMC code, is used for the micro-level analysis. First, a baseline study of MAC/GMC is performed to determine the governing failure theories that best capture the damage progression. The deficiencies associated with various layups and loading conditions are addressed. In most micromechanics analysis, a representative unit cell (RUC) with a common fiber packing arrangement is used. The effect of variation in this arrangement within the RUC has been studied and results indicate this variation influences the macro-scale effective material properties and failure stresses. The developed model has been used to simulate impact damage in a composite beam and an airfoil structure. The model data was verified through active interrogation using piezoelectric sensors. The multiscale model was further extended to develop a coupled damage and wave attenuation model, which was used to study different damage states such as fiber-matrix debonding in composite structures with surface bonded piezoelectric sensors.
ContributorsMoncada, Albert (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Yekani Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2012
Description
Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.
ContributorsZou, Jin (Author) / Dai, Lenore L (Thesis advisor) / Chattopadhyay, Aditi (Thesis advisor) / Lind, Mary L (Committee member) / Mu, Bin (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
Description
Advanced composites are being widely used in aerospace applications due to their high stiffness, strength and energy absorption capabilities. However, the assurance of structural reliability is a critical issue because a damage event will compromise the integrity of composite structures and lead to ultimate failure. In this dissertation a novel homogenization based multiscale modeling framework using semi-analytical micromechanics is presented to simulate the response of textile composites. The novelty of this approach lies in the three scale homogenization/localization framework bridging between the constituent (micro), the fiber tow scale (meso), weave scale (macro), and the global response. The multiscale framework, named Multiscale Generalized Method of Cells (MSGMC), continuously bridges between the micro to the global scale as opposed to approaches that are top-down and bottom-up. This framework is fully generalized and capable of modeling several different weave and braids without reformulation. Particular emphasis in this dissertation is placed on modeling the nonlinearity and failure of both polymer matrix and ceramic matrix composites.
ContributorsLiu, Guang (Author) / Chattopadhyay, Aditi (Thesis advisor) / Mignolet, Marc (Committee member) / Jiang, Hanqing (Committee member) / Li, Jian (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Nanoparticles are ubiquitous in various fields due to their unique properties not seen in similar bulk materials. Among them, core-shell composite nanoparticles are an important class of materials which are attractive for their applications in catalysis, sensing, electromagnetic shielding, drug delivery, and environmental remediation. This dissertation focuses on the study of core-shell type of nanoparticles where a polymer serves as the core and inorganic nanoparticles are the shell. This is an interesting class of supramolecular building blocks and can "exhibit unusual, possibly unique, properties which cannot be obtained simply by co-mixing polymer and inorganic particles". The one-step Pickering emulsion polymerization method was successfully developed and applied to synthesize polystyrene-silica core-shell composite particles. Possible mechanisms of the Pickering emulsion polymerization were also explored. The silica nanoparticles were thermodynamically favorable to self-assemble at liquid-liquid interfaces at the initial stage of polymerization and remained at the interface to finally form the shells of the composite particles. More importantly, Pickering emulsion polymerization was employed to synthesize polystyrene/poly(N-isopropylacrylamide) (PNIPAAm)-silica core-shell nanoparticles with N-isopropylacrylamide incorporated into the core as a co-monomer. The composite nanoparticles were temperature sensitive and could be up-taken by human prostate cancer cells and demonstrated effectiveness in drug delivery and cancer therapy. Similarly, by incorporating poly-2-(N,N)-dimethylamino)ethyl methacrylate (PDMA) into the core, pH sensitive core-shell composite nanoparticles were synthesized and applied as effective carriers to release a rheological modifier upon a pH change. Finally, the research focuses on facile approaches to engineer the transition of the temperature-sensitive particles and develop composite core-shell nanoparticles with a metallic shell.
ContributorsSanyal, Sriya (Author) / Dai, Lenore L. (Thesis advisor) / Jiang, Hanqing (Committee member) / Lind, Mary L. (Committee member) / Phelan, Patrick (Committee member) / Rege, Kaushal (Committee member) / Arizona State University (Publisher)
Created2012
Description
Environmentally responsive microgels have drawn significant attention due to their intrinsic ability to change volume in response to various external stimuli such as pH, temperature, osmotic pressure, or electric and magnetic fields. The extent of particle swelling is controlled by the nature of the polymer-solvent interaction. This thesis focuses on design and synthesis of environmentally responsive microgels and their composites, and encompasses methods of utilizing microgel systems in applications as vehicles for the adsorption, retention, and targeted delivery of chemical species. Furthermore, self-assembled microgel particles at ionic liquid (IL)-water interfaces demonstrate responsive colloidal lattice morphology. The thesis first reports on the fundamental aspects of synthesis, functionalization, and characteristic properties of multifunctional environmentally responsive microgels derived from poly(N-isopropylacrylamide) (PNIPAm) and other functional co-monomers. In particular, the uptake and release of active chemical species such as rheology modifiers into and from these ionic microgels is demonstrated. Moreover, a facile tunable method for the formation of organic-inorganic composites with Fe3O4 nanoparticles adsorbed and embedded within ionic microgel particles is explored. Additionally, the development of zwitterionic microgels (ZI-MG) is presented. These aqueous ZI-MG dispersions exhibit reversible parabolic swelling as a function of pH and display a minimum hydrodynamic diameter at a tunable isoelectric point (IEP). This study also elucidates the controlled uptake and release of surfactants from these particle systems. The extent of surfactant loading and the ensuing relative swelling/deswelling behaviors within the polymer networks are explained in terms of their binding interactions. The latter part of this thesis highlights the versatility of fluorescently labeled microgel particles as stabilizers for IL-water droplets. When the prepared particles form monolayers and equilibrate at the liquid-liquid interface, the colloidal lattice organization may re-order itself depending on the surface charge of these particles. Finally, it is shown that the spontaneously formed and densely packed layers of microgel particles can be employed for extraction applications, as the interface remains permeable to small active species.
ContributorsChen, Haobo (Author) / Dai, Lenore L (Committee member) / Chen, Kangping (Committee member) / Forzani, Erica (Committee member) / Lind, Mary Laura (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2015
Description
The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials with complex internal geometries. A key contribution of this work is the creation of novel methods designed to automate the incorporation of high-resolution data, e.g. from X-ray tomography, that can be used to better interpret the enormous volume of data generated in modern in-situ experimental testing. Thus new algorithms were developed for automating analysis of complex microstructures characterized by segmented tomographic images.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
ContributorsYuan, Rui (Author) / Oswald, Jay (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Solanki, Kiran (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
Description
Polymer-gold composite particles are of tremendous research interests. Contributed by their unique structures, these particles demonstrate superior properties for optical, catalytic and electrical applications. Moreover, the incorporation of “smart” polymers into polymer-gold composite particles enables the composite particles synergistically respond to environment-stimuli like temperature, pH and light with promising applications in multiple areas.
A novel Pickering emulsion polymerization route is found for synthesis of core-shell structured polymer-gold composite particles. It is found that the surface coverage of gold nanoparticles (AuNP) on a polystyrene core is influenced by gold nanoparticle concentration and hydrophobicity. More importantly, the absorption wavelength of polystyrene-gold composite particles is tunable by adjusting AuNP interparticle distance. Further, core-shell structured polystyrene-gold composite particles demonstrate excellent catalyst recyclability.
Asymmetric polystyrene-gold composite particles are successfully synthesized via seeded emulsion polymerization, where AuNPs serve as seeds, allowing the growth of styrene monomers/oligomers on them. These particles also demonstrate excellent catalyst recyclability. Further, monomers of “smart” polymers, poly (N-isopropylacrylamide) (PNIPAm), are successfully copolymerized into asymmetric composite particles, enabling these particles’ thermo-responsiveness with significant size variation around lower critical solution temperature (LCST) of 31°C. The significant size variation gives rise to switchable scattering intensity property, demonstrating potential applications in intensity-based optical sensing.
Multipetal and dumbbell structured gold-polystyrene composite particles are also successfully synthesized via seeded emulsion polymerization. It is intriguing to observe that by controlling reaction time and AuNP size, tetrapetal-structured, tripetal-structured and dumbbell-structured gold-polystyrene are obtained. Further, “smart” PNIPAm polymers are successfully copolymerized into dumbbell-shaped particles, showing significant size variation around LCST. Self-modulated catalytic activity around LCST is achieved for these particles. It is hypothesized that above LCST, the significant shrinkage of particles limits diffusion of reaction molecules to the surface of AuNPs, giving a reduced catalytic activity.
Finally, carbon black (CB) particles are successfully employed for synthesis of core- shell PNIPAm/polystyrene-CB particles. The thermo-responsive absorption characteristics of PNIPAm/polystyrene-CB particles enable them potentially suitable to serve as “smart” nanofluids with self-controlled temperature. Compared to AuNPs, CB particles provide desirable performance here, because they show no plasmon resonance in visible wavelength range, whereas AuNPs’ absorption in the visible wavelength range is undesirable.
A novel Pickering emulsion polymerization route is found for synthesis of core-shell structured polymer-gold composite particles. It is found that the surface coverage of gold nanoparticles (AuNP) on a polystyrene core is influenced by gold nanoparticle concentration and hydrophobicity. More importantly, the absorption wavelength of polystyrene-gold composite particles is tunable by adjusting AuNP interparticle distance. Further, core-shell structured polystyrene-gold composite particles demonstrate excellent catalyst recyclability.
Asymmetric polystyrene-gold composite particles are successfully synthesized via seeded emulsion polymerization, where AuNPs serve as seeds, allowing the growth of styrene monomers/oligomers on them. These particles also demonstrate excellent catalyst recyclability. Further, monomers of “smart” polymers, poly (N-isopropylacrylamide) (PNIPAm), are successfully copolymerized into asymmetric composite particles, enabling these particles’ thermo-responsiveness with significant size variation around lower critical solution temperature (LCST) of 31°C. The significant size variation gives rise to switchable scattering intensity property, demonstrating potential applications in intensity-based optical sensing.
Multipetal and dumbbell structured gold-polystyrene composite particles are also successfully synthesized via seeded emulsion polymerization. It is intriguing to observe that by controlling reaction time and AuNP size, tetrapetal-structured, tripetal-structured and dumbbell-structured gold-polystyrene are obtained. Further, “smart” PNIPAm polymers are successfully copolymerized into dumbbell-shaped particles, showing significant size variation around LCST. Self-modulated catalytic activity around LCST is achieved for these particles. It is hypothesized that above LCST, the significant shrinkage of particles limits diffusion of reaction molecules to the surface of AuNPs, giving a reduced catalytic activity.
Finally, carbon black (CB) particles are successfully employed for synthesis of core- shell PNIPAm/polystyrene-CB particles. The thermo-responsive absorption characteristics of PNIPAm/polystyrene-CB particles enable them potentially suitable to serve as “smart” nanofluids with self-controlled temperature. Compared to AuNPs, CB particles provide desirable performance here, because they show no plasmon resonance in visible wavelength range, whereas AuNPs’ absorption in the visible wavelength range is undesirable.
ContributorsZhang, Mingmeng (Author) / Dai, Lenore L (Committee member) / Phelan, Patrick E (Committee member) / Otanicar, Todd P (Committee member) / Lin, Jerry (Committee member) / He, Ximin (Committee member) / Arizona State University (Publisher)
Created2015
Description
The problem of catastrophic damage purveys in any material application, and minimizing its occurrence is paramount for general health and safety. Thus, novel damage detection schemes are required that can sense the precursors to damage. Mechanochemistry is the area of research that involves the use of mechanical force to induce a chemical change, with recent study focusing on directing the mechanical force to embedded mechanophore units for a targeted chemical response. Mechanophores are molecular units that provide a measureable signal in response to an applied force, often in the form of a visible color change or fluorescent emission, and their application to thermoset network polymers has been limited. Following preliminary work on polymer blends of cyclobutane-based mechanophores and epoxy, dimeric 9-anthracene carboxylic acid (Di-AC)-based mechanophore particles were synthesized and employed to form stress sensitive particle reinforced epoxy matrix composites.
Under an applied stress, the cyclooctane-rings in the Di-AC particles revert back to their fluorescent anthracene form, which linearly enhances the overall fluorescence of the composite in response to the applied strain. The fluorescent signal further allows for stress sensing in the elastic region of the stress-strain curve, which is considered to be a form of damage precursor detection. This behavior was further analyzed at the molecular scale with corresponding molecular dynamics simulations. Following the successful application of Di-AC to an epoxy matrix, the mechanophore particles were incorporated into a polyurethane matrix to show the universal nature of Di-AC as a stress-sensitive particle filler. Interestingly, in polyurethane Di-AC could successfully detect damage with less applied strain compared to the epoxy system.
While mechanophores of varying chemistries have been covalently incorporated into elastomeric and thermoplastic polymer systems, they have not yet been covalently incorporated a thermoset network polymer. Thus, following the study of mechanophore particles as stress-sensitive fillers, two routes of grafting mechanophore units into an epoxy system to form a self-sensing nanocomposite were explored. These involved the mechanophore precursor and mechanophore, cinnamamide and di-cinnamamide, respectively. With both molecules, the free amine groups can directly bond to epoxy resin to covalently incorporate themselves within the thermoset network to form a self-sensing nanocomposite.
Under an applied stress, the cyclooctane-rings in the Di-AC particles revert back to their fluorescent anthracene form, which linearly enhances the overall fluorescence of the composite in response to the applied strain. The fluorescent signal further allows for stress sensing in the elastic region of the stress-strain curve, which is considered to be a form of damage precursor detection. This behavior was further analyzed at the molecular scale with corresponding molecular dynamics simulations. Following the successful application of Di-AC to an epoxy matrix, the mechanophore particles were incorporated into a polyurethane matrix to show the universal nature of Di-AC as a stress-sensitive particle filler. Interestingly, in polyurethane Di-AC could successfully detect damage with less applied strain compared to the epoxy system.
While mechanophores of varying chemistries have been covalently incorporated into elastomeric and thermoplastic polymer systems, they have not yet been covalently incorporated a thermoset network polymer. Thus, following the study of mechanophore particles as stress-sensitive fillers, two routes of grafting mechanophore units into an epoxy system to form a self-sensing nanocomposite were explored. These involved the mechanophore precursor and mechanophore, cinnamamide and di-cinnamamide, respectively. With both molecules, the free amine groups can directly bond to epoxy resin to covalently incorporate themselves within the thermoset network to form a self-sensing nanocomposite.
ContributorsNofen, Elizabeth (Author) / Dai, Lenore L (Thesis advisor) / Chattopadhyay, Aditi (Thesis advisor) / Emady, Heather (Committee member) / Mu, Bin (Committee member) / Nielsen, David (Committee member) / Arizona State University (Publisher)
Created2016
Description
In-situ fatigue damage diagnosis and prognosis is a challenging problem for both metallic and composite materials and structures. There are various uncertainties arising from material properties, component geometries, measurement noise, feature extraction techniques, and modeling errors. It is essential to manage and incorporate these uncertainties in order to achieve accurate damage detection and remaining useful life (RUL) prediction.
The aim of this study is to develop an integrated fatigue damage diagnosis and prognosis framework for both metallic and composite materials. First, Lamb waves are used as the in-situ damage detection technique to interrogate the damaged structures. Both experimental and numerical analysis for the Lamb wave propagation within aluminum are conducted. The RUL of lap joints under variable and constant fatigue loading is predicted using the Bayesian updating by incorporating damage detection information and various sources of uncertainties. Following this, the effect of matrix cracking and delamination in composite laminates on the Lamb wave propagation is investigated and a generalized probabilistic delamination size and location detection framework using Bayesian imaging method (BIM) is proposed and validated using the composite fatigue testing data. The RUL of the open-hole specimen is predicted using the overall stiffness degradation under fatigue loading. Next, the adjoint method-based damage detection framework is proposed considering the physics of heat conduction or elastic wave propagation. Different from the classical wave propagation-based method, the received signal under pristine condition is not necessary for estimating the damage information. This method can be successfully used for arbitrary damage location and shape profiling for any materials with higher accuracy and resolution. Finally, some conclusions and future work are generated based on the current investigation.
The aim of this study is to develop an integrated fatigue damage diagnosis and prognosis framework for both metallic and composite materials. First, Lamb waves are used as the in-situ damage detection technique to interrogate the damaged structures. Both experimental and numerical analysis for the Lamb wave propagation within aluminum are conducted. The RUL of lap joints under variable and constant fatigue loading is predicted using the Bayesian updating by incorporating damage detection information and various sources of uncertainties. Following this, the effect of matrix cracking and delamination in composite laminates on the Lamb wave propagation is investigated and a generalized probabilistic delamination size and location detection framework using Bayesian imaging method (BIM) is proposed and validated using the composite fatigue testing data. The RUL of the open-hole specimen is predicted using the overall stiffness degradation under fatigue loading. Next, the adjoint method-based damage detection framework is proposed considering the physics of heat conduction or elastic wave propagation. Different from the classical wave propagation-based method, the received signal under pristine condition is not necessary for estimating the damage information. This method can be successfully used for arbitrary damage location and shape profiling for any materials with higher accuracy and resolution. Finally, some conclusions and future work are generated based on the current investigation.
ContributorsPeng, Tishun (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Mignolet, Marc (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Tang, Pingbo (Committee member) / Arizona State University (Publisher)
Created2016
Description
Nanolaminate composite materials consist of alternating layers of materials at the nanoscale (≤100 nm). Due to the nanometer scale thickness of their layers, these materials display unique and tailorable properties. This enables us to alter both mechanical attributes such as strength and wear properties, as well as functional characteristics such as biocompatibility, optical, and electronic properties. This dissertation focuses on understanding the mechanical behavior of the Al-SiC system. From a practical perspective, these materials exhibit a combination of high toughness and strength which is attractive for many applications. Scientifically, these materials are interesting due to the large elastic modulus mismatch between the layers. This, paired with the small layer thickness, allows a unique opportunity for scientists to study the plastic deformation of metals under extreme amounts of constraint.
Previous studies are limited in scope and a more diverse range of mechanical characterization is required to understand both the advantages and limitations of these materials. One of the major challenges with testing these materials is that they are only able to be made in thicknesses on the order of micrometers so the testing methods are limited to small volume techniques. This work makes use of both microscale testing techniques from the literature as well as novel methodologies. Using these techniques we are able to gain insight into aspects of the material’s mechanical behavior such as the effects of layer orientation, flaw dependent fracture, tension-compression asymmetry, fracture toughness as a function of layer thickness, and shear behavior as a function of layer thickness.
Previous studies are limited in scope and a more diverse range of mechanical characterization is required to understand both the advantages and limitations of these materials. One of the major challenges with testing these materials is that they are only able to be made in thicknesses on the order of micrometers so the testing methods are limited to small volume techniques. This work makes use of both microscale testing techniques from the literature as well as novel methodologies. Using these techniques we are able to gain insight into aspects of the material’s mechanical behavior such as the effects of layer orientation, flaw dependent fracture, tension-compression asymmetry, fracture toughness as a function of layer thickness, and shear behavior as a function of layer thickness.
ContributorsMayer, Carl Randolph (Author) / Chawla, Nikhilesh (Thesis advisor) / Jiang, Hanqing (Committee member) / Molina-Aldareguia, Jon (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2016