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Description
Fission products in nuclear fuel pellets can affect fuel performance as they change the fuel chemistry and structure. The behavior of the fission products and their release mechanisms are important to the operation of a power reactor. Research has shown that fission product release can occur through grain boundary (GB) at low burnups. Early fission gas release models, which assumed spherical grains with no effect of GB diffusion, did not capture the early stage of the release behavior well. In order to understand the phenomenon at low burnup and how it leads to the later release mechanism, a microstructurally explicit model is needed. This dissertation conducted finite element simulations of the transport behavior using 3-D microstructurally explicit models. It looks into the effects of GB character, with emphases on conditions that can lead to enhanced effective diffusion. Moreover, the relationship between temperature and fission product transport is coupled to reflect the high temperature environment.
The modeling work began with 3-D microstructure reconstruction for three uranium oxide samples with different oxygen stoichiometry: UO2.00 UO2.06 and UO2.14. The 3-D models were created based on the real microstructure of depleted UO2 samples characterized by Electron Backscattering Diffraction (EBSD) combined with serial sectioning. Mathematical equations on fission gas diffusion and heat conduction were studied and derived to simulate the fission gas transport under GB effect. Verification models showed that 2-D elements can be used to model GBs to reduce the number of elements. The effect of each variable, including fuel stoichiometry, temperature, GB diffusion, triple junction diffusion and GB thermal resistance, is verified, and they are coupled in multi-physics simulations to study the transport of fission gas at different radial location of a fuel pellet. It was demonstrated that the microstructural model can be used to incorporate the effect of different physics to study fission gas transport. The results suggested that the GB effect is the most significant at the edge of fuel pellet where the temperature is the lowest. In the high temperature region, the increase in bulk diffusivity due to excess oxygen diminished the effect of GB diffusion.
The modeling work began with 3-D microstructure reconstruction for three uranium oxide samples with different oxygen stoichiometry: UO2.00 UO2.06 and UO2.14. The 3-D models were created based on the real microstructure of depleted UO2 samples characterized by Electron Backscattering Diffraction (EBSD) combined with serial sectioning. Mathematical equations on fission gas diffusion and heat conduction were studied and derived to simulate the fission gas transport under GB effect. Verification models showed that 2-D elements can be used to model GBs to reduce the number of elements. The effect of each variable, including fuel stoichiometry, temperature, GB diffusion, triple junction diffusion and GB thermal resistance, is verified, and they are coupled in multi-physics simulations to study the transport of fission gas at different radial location of a fuel pellet. It was demonstrated that the microstructural model can be used to incorporate the effect of different physics to study fission gas transport. The results suggested that the GB effect is the most significant at the edge of fuel pellet where the temperature is the lowest. In the high temperature region, the increase in bulk diffusivity due to excess oxygen diminished the effect of GB diffusion.
ContributorsLim, Harn Chyi (Author) / Peralta, Pedro (Thesis advisor) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2014
Description
An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for quantitative structure-property relations establishment and its performance prediction and optimization. X-ray tomography has provided a non-destructive means for microstructure characterization in both 3D and 4D (i.e., structural evolution over time). Traditional reconstruction algorithms like filtered-back-projection (FBP) method or algebraic reconstruction techniques (ART) require huge number of tomographic projections and segmentation process before conducting microstructural quantification. This can be quite time consuming and computationally intensive.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.
ContributorsLi, Hechao (Author) / Jiao, Yang (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Ren, Yi (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Very High Temperature Reactor (VHTR) is one of six conceptual designs proposed for Generation IV nuclear reactors. Alloy 617, a solid solution strengthened Ni-base superalloy, is currently the primary candidate material for the tubing of the Intermediate Heat Exchanger (IHX) in the VHTR design. Steady-state operation of the nuclear power plant at elevated temperatures leads to creep deformation, whereas loading transients including startup and shutdown generate fatigue. A detailed understanding of the creep-fatigue interaction in Alloy 617 is necessary before it can be considered as a material for nuclear construction in ASME Boiler and Pressure Vessel Code. Current design codes for components undergoing creep-fatigue interaction at elevated temperatures require creep-fatigue testing data covering the entire range from fatigue-dominant to creep-dominant loading. Classical strain-controlled tests, which produce stress relaxation during the hold period, show a saturation in cycle life with increasing hold periods due to the rapid stress-relaxation of Alloy 617 at high temperatures. Therefore, applying longer hold time in these tests cannot generate creep-dominated failure. In this study, uniaxial isothermal creep-fatigue tests with non-traditional loading waveforms were designed and performed at 850 and 950°C, with an objective of generating test data in the creep-dominant regime. The new loading waveforms are hybrid strain-controlled and force-controlled testing which avoid stress relaxation during the creep hold. The experimental data showed varying proportions of creep and fatigue damage, and provided evidence for the inadequacy of the widely-used time fraction rule for estimating creep damage under creep-fatigue conditions. Micro-scale damage features in failed test specimens, such as fatigue cracks and creep voids, were quantified using a Scanning Electron Microscope (SEM) to find a correlation between creep and fatigue damage. Quantitative statistical imaging analysis showed that the microstructural damage features (cracks and voids) are correlated with a new mechanical driving force parameter. The results from this image-based damage analysis were used to develop a phenomenological life-prediction methodology called the effective time fraction approach. Finally, the constitutive creep-fatigue response of the material at 950°C was modeled using a unified viscoplastic model coupled with a damage accumulation model. The simulation results were used to validate an energy-based constitutive life-prediction model, as a mechanistic model for potential component and structure level creep-fatigue analysis.
ContributorsTahir, Fraaz (Author) / Liu, Yongming (Thesis advisor) / Jiang, Hanqing (Committee member) / Rajagopalan, Jagannathan (Committee member) / Oswald, Jay (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2017
Description
Aluminum alloys are ubiquitously used in almost all structural applications due to their high strength-to-weight ratio. Their superior mechanical performance can be attributed to complex dispersions of nanoscale intermetallic particles that precipitate out from the alloy’s solid solution and offer resistance to deformation. Although they have been extensively investigated in the last century, the traditional approaches employed in the past haven’t rendered an authoritative microstructural understanding in such materials. The effect of the precipitates’ inherent complex morphology and their three-dimensional (3D) spatial distribution on evolution and deformation behavior have often been precluded. In this study, for the first time, synchrotron-based hard X-ray nano-tomography has been implemented in Al-Cu alloys to measure growth kinetics of different nanoscale phases in 3D and reveal mechanistic insights behind some of the observed novel phase transformation reactions occurring at high temperatures. The experimental results were reconciled with coarsening models from the LSW theory to an unprecedented extent, thereby establishing a new paradigm for thermodynamic analysis of precipitate assemblies. By using a unique correlative approach, a non-destructive means of estimating precipitation-strengthening in such alloys has been introduced. Limitations of using existing mechanical strengthening models in such alloys have been discussed and a means to quantify individual contributions from different strengthening mechanisms has been established.
The current rapid pace of technological progress necessitates the demand for more resilient and high-performance alloys. To achieve this, a thorough understanding of the relationships between material properties and its structure is indispensable. To establish this correlation and achieve desired properties from structural alloys, microstructural response to mechanical stimuli needs to be understood in three-dimensions (3D). To that effect, in situ tests were conducted at the synchrotron (Advanced Photon Source) using Transmission X-Ray Microscopy as well as in a scanning electron microscope (SEM) to study real-time damage evolution in such alloys. Findings of precipitate size-dependent transition in deformation behavior from these tests have inspired a novel resilient aluminum alloy design.
The current rapid pace of technological progress necessitates the demand for more resilient and high-performance alloys. To achieve this, a thorough understanding of the relationships between material properties and its structure is indispensable. To establish this correlation and achieve desired properties from structural alloys, microstructural response to mechanical stimuli needs to be understood in three-dimensions (3D). To that effect, in situ tests were conducted at the synchrotron (Advanced Photon Source) using Transmission X-Ray Microscopy as well as in a scanning electron microscope (SEM) to study real-time damage evolution in such alloys. Findings of precipitate size-dependent transition in deformation behavior from these tests have inspired a novel resilient aluminum alloy design.
ContributorsKaira, Chandrashekara Shashank (Author) / Chawla, Nikhilesh (Thesis advisor) / Solanki, Kiran (Committee member) / Jiao, Yang (Committee member) / De Andrade, Vincent (Committee member) / Arizona State University (Publisher)
Created2017
Description
Interstitial impurity atoms can significantly alter the chemical and physical properties of the host material. Oxygen impurity in HCP titanium is known to have a considerable strengthening effect mainly through interactions with dislocations. To better understand such an effect, first the role of oxygen on various slip planes in titanium is examined using generalized stacking fault energies (GSFE) computed by the first principles calculations. It is shown that oxygen can significantly increase the energy barrier to dislocation motion on most of the studied slip planes. Then the Peierls-Nabbaro model is utilized in conjunction with the GSFE to estimate the Peierls stress ratios for different slip systems. Using such information along with a set of tension and compression experiments, the parameters of a continuum scale crystal plasticity model, namely CRSS values, are calibrated. Effect of oxygen content on the macroscopic stress-strain response is further investigated through experiments on oxygen-boosted samples at room temperature. It is demonstrated that the crystal plasticity model can very well capture the effect of oxygen content on the global response of the samples. It is also revealed that oxygen promotes the slip activity on the pyramidal planes.
The effect of oxygen impurity on titanium is further investigated under high cycle fatigue loading. For that purpose, a two-step hierarchical crystal plasticity for fatigue predictions is presented. Fatigue indicator parameter is used as the main driving force in an energy-based crack nucleation model. To calculate the FIPs, high-resolution full-field crystal plasticity simulations are carried out using a spectral solver. A nucleation model is proposed and calibrated by the fatigue experimental data for notched titanium samples with different oxygen contents and under two load ratios. Overall, it is shown that the presented approach is capable of predicting the high cycle fatigue nucleation time. Moreover, qualitative predictions of microstructurally small crack growth rates are provided. The multi-scale methodology presented here can be extended to other material systems to facilitate a better understanding of the fundamental deformation mechanisms, and to effectively implement such knowledge in mesoscale-macroscale investigations.
The effect of oxygen impurity on titanium is further investigated under high cycle fatigue loading. For that purpose, a two-step hierarchical crystal plasticity for fatigue predictions is presented. Fatigue indicator parameter is used as the main driving force in an energy-based crack nucleation model. To calculate the FIPs, high-resolution full-field crystal plasticity simulations are carried out using a spectral solver. A nucleation model is proposed and calibrated by the fatigue experimental data for notched titanium samples with different oxygen contents and under two load ratios. Overall, it is shown that the presented approach is capable of predicting the high cycle fatigue nucleation time. Moreover, qualitative predictions of microstructurally small crack growth rates are provided. The multi-scale methodology presented here can be extended to other material systems to facilitate a better understanding of the fundamental deformation mechanisms, and to effectively implement such knowledge in mesoscale-macroscale investigations.
ContributorsGholami Bazehhour, Benyamin (Author) / Solanki, Kiran N (Thesis advisor) / Liu, Yongming (Committee member) / Oswald, Jay J (Committee member) / Rajagopalan, Jagannathan (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
In material science, microstructure plays a key role in determining properties, which further determine utility of the material. However, effectively measuring microstructure evolution in real time remains an challenge. To date, a wide range of advanced experimental techniques have been developed and applied to characterize material microstructure and structural evolution on different length and time scales. Most of these methods can only resolve 2D structural features within a narrow range of length scale and for a single or a series of snapshots. The currently available 3D microstructure characterization techniques are usually destructive and require slicing and polishing the samples each time a picture is taken. Simulation methods, on the other hand, are cheap, sample-free and versatile without the special necessity of taking care of the physical limitations, such as extreme temperature or pressure, which are prominent
issues for experimental methods. Yet the majority of simulation methods are limited to specific circumstances, for example, first principle computation can only handle several thousands of atoms, molecular dynamics can only efficiently simulate a few seconds of evolution of a system with several millions particles, and finite element method can only be used in continuous medium, etc. Such limitations make these individual methods far from satisfaction to simulate macroscopic processes that a material sample undergoes up to experimental level accuracy. Therefore, it is highly desirable to develop a framework that integrate different simulation schemes from various scales
to model complicated microstructure evolution and corresponding properties. Guided by such an objective, we have made our efforts towards incorporating a collection of simulation methods, including finite element method (FEM), cellular automata (CA), kinetic Monte Carlo (kMC), stochastic reconstruction method, Discrete Element Method (DEM), etc, to generate an integrated computational material engineering platform (ICMEP), which could enable us to effectively model microstructure evolution and use the simulated microstructure to do subsequent performance analysis. In this thesis, we will introduce some cases of building coupled modeling schemes and present
the preliminary results in solid-state sintering. For example, we use coupled DEM and kinetic Monte Carlo method to simulate solid state sintering, and use coupled FEM and cellular automata method to model microstrucutre evolution during selective laser sintering of titanium alloy. Current results indicate that joining models from different length and time scales is fruitful in terms of understanding and describing microstructure evolution of a macroscopic physical process from various perspectives.
issues for experimental methods. Yet the majority of simulation methods are limited to specific circumstances, for example, first principle computation can only handle several thousands of atoms, molecular dynamics can only efficiently simulate a few seconds of evolution of a system with several millions particles, and finite element method can only be used in continuous medium, etc. Such limitations make these individual methods far from satisfaction to simulate macroscopic processes that a material sample undergoes up to experimental level accuracy. Therefore, it is highly desirable to develop a framework that integrate different simulation schemes from various scales
to model complicated microstructure evolution and corresponding properties. Guided by such an objective, we have made our efforts towards incorporating a collection of simulation methods, including finite element method (FEM), cellular automata (CA), kinetic Monte Carlo (kMC), stochastic reconstruction method, Discrete Element Method (DEM), etc, to generate an integrated computational material engineering platform (ICMEP), which could enable us to effectively model microstructure evolution and use the simulated microstructure to do subsequent performance analysis. In this thesis, we will introduce some cases of building coupled modeling schemes and present
the preliminary results in solid-state sintering. For example, we use coupled DEM and kinetic Monte Carlo method to simulate solid state sintering, and use coupled FEM and cellular automata method to model microstrucutre evolution during selective laser sintering of titanium alloy. Current results indicate that joining models from different length and time scales is fruitful in terms of understanding and describing microstructure evolution of a macroscopic physical process from various perspectives.
ContributorsChen, Shaohua (Author) / Jiao, Yang (Thesis advisor) / Wang, Qinghua (Committee member) / Emady, Heather (Committee member) / Gel, Aytekin (Committee member) / Arizona State University (Publisher)
Created2018
Description
Metal Organic Frameworks(MOFs) have been used in various applications, including
sensors. The unique crystalline structure of MOFs in addition to controllability of
their pore size and their intake selectivity makes them a promising method of detection.
Detection of metal ions in water using a binary mixture of luminescent MOFs
has been reported. 3 MOFs(ZrPDA, UiO-66 and UiO-66-NH2) as detectors and 4
metal ions(Pb2+, Ni2+, Ba2+ and Cu2+) as the target species were chosen based on
cost, water stability, application and end goals.
It is possible to detect metal ions such as Pb2+ at concentrations at low as 0.005
molar using MOFs. Also, based on the luminescence responses, a method of distinguishing
between similar metal ions has been proposed. It is shown that using a
mixture of MOFs with dierent reaction to metal ions can lead to unique and specic
3D luminescence maps, which can be used to identify the present metal ions in water
and their amount.
In addition to the response of a single MOF to addition of a single metal ion,
luminescence response of ZrPDA + UiO-66 mixture to increasing concentration of
each of 4 metal ions was studied, and summarized. A new peak is observed in the
mixture, that did not exist before, and it is proposed that this peak requires metal
ions to activate
sensors. The unique crystalline structure of MOFs in addition to controllability of
their pore size and their intake selectivity makes them a promising method of detection.
Detection of metal ions in water using a binary mixture of luminescent MOFs
has been reported. 3 MOFs(ZrPDA, UiO-66 and UiO-66-NH2) as detectors and 4
metal ions(Pb2+, Ni2+, Ba2+ and Cu2+) as the target species were chosen based on
cost, water stability, application and end goals.
It is possible to detect metal ions such as Pb2+ at concentrations at low as 0.005
molar using MOFs. Also, based on the luminescence responses, a method of distinguishing
between similar metal ions has been proposed. It is shown that using a
mixture of MOFs with dierent reaction to metal ions can lead to unique and specic
3D luminescence maps, which can be used to identify the present metal ions in water
and their amount.
In addition to the response of a single MOF to addition of a single metal ion,
luminescence response of ZrPDA + UiO-66 mixture to increasing concentration of
each of 4 metal ions was studied, and summarized. A new peak is observed in the
mixture, that did not exist before, and it is proposed that this peak requires metal
ions to activate
ContributorsSirous, Peyman (Author) / Mu, Bin (Thesis advisor) / Alford, Terry (Thesis advisor) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
Increasing density of microelectronic packages, results in an increase in thermal and mechanical stresses within the various layers of the package. To accommodate the high-performance demands, the materials used in the electronic package would also require improvement. Specifically, the damage that often occurs in solders that function as die-attachment and thermal interfaces need to be addressed. This work evaluates and characterizes thermo-mechanical damage in two material systems – Electroplated Tin and Sintered Nano-Silver solder.
Tin plated electrical contacts are prone to formation of single crystalline tin whiskers which can cause short circuiting. A mechanistic model of their formation, evolution and microstructural influence is still not fully understood. In this work, growth of mechanically induced tin whiskers/hillocks is studied using in situ Nano-indentation and Electron Backscatter Diffraction (EBSD). Electroplated tin was indented and monitored in vacuum to study growth of hillocks without the influence of atmosphere. Thermal aging was done to study the effect of intermetallic compounds. Grain orientation of the hillocks and the plastically deformed region surrounding the indent was studied using Focused Ion Beam (FIB) lift-out technique. In addition, micropillars were milled on the surface of electroplated Sn using FIB to evaluate the yield strength and its relation to Sn grain size.
High operating temperature power electronics use wide band-gap semiconductor devices (Silicon Carbide/Gallium Nitride). The operating temperature of these devices can exceed 250oC, preventing use of traditional Sn-solders as Thermal Interface materials (TIM). At high temperature, the thermomechanical stresses can severely degrade the reliability and life of the device. In this light, new non-destructive approach is needed to understand the damage mechanism when subjected to reliability tests such as thermal cycling. In this work, sintered nano-Silver was identified as a promising high temperature TIM. Sintered nano-Silver samples were fabricated and their shear strength was evaluated. Thermal cycling tests were conducted and damage evolution was characterized using a lab scale 3D X-ray system to periodically assess changes in the microstructure such as cracks, voids, and porosity in the TIM layer. The evolution of microstructure and the effect of cycling temperature during thermal cycling are discussed.
Tin plated electrical contacts are prone to formation of single crystalline tin whiskers which can cause short circuiting. A mechanistic model of their formation, evolution and microstructural influence is still not fully understood. In this work, growth of mechanically induced tin whiskers/hillocks is studied using in situ Nano-indentation and Electron Backscatter Diffraction (EBSD). Electroplated tin was indented and monitored in vacuum to study growth of hillocks without the influence of atmosphere. Thermal aging was done to study the effect of intermetallic compounds. Grain orientation of the hillocks and the plastically deformed region surrounding the indent was studied using Focused Ion Beam (FIB) lift-out technique. In addition, micropillars were milled on the surface of electroplated Sn using FIB to evaluate the yield strength and its relation to Sn grain size.
High operating temperature power electronics use wide band-gap semiconductor devices (Silicon Carbide/Gallium Nitride). The operating temperature of these devices can exceed 250oC, preventing use of traditional Sn-solders as Thermal Interface materials (TIM). At high temperature, the thermomechanical stresses can severely degrade the reliability and life of the device. In this light, new non-destructive approach is needed to understand the damage mechanism when subjected to reliability tests such as thermal cycling. In this work, sintered nano-Silver was identified as a promising high temperature TIM. Sintered nano-Silver samples were fabricated and their shear strength was evaluated. Thermal cycling tests were conducted and damage evolution was characterized using a lab scale 3D X-ray system to periodically assess changes in the microstructure such as cracks, voids, and porosity in the TIM layer. The evolution of microstructure and the effect of cycling temperature during thermal cycling are discussed.
ContributorsLujan Regalado, Irene (Author) / Chawla, Nikhilesh (Thesis advisor) / Frear, Darrel (Committee member) / Rajagopalan, Jagannathan (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
With the maturity of advanced composites as feasible structural materials for various applications there is a critical need to solve the challenge of designing these material systems for optimal performance. However, determining superior design methods requires a deep understanding of the material-structure properties at various length scales. Due to the length-scale dependent behavior of advanced composites, multiscale modeling techniques may be used to describe the dominant mechanisms of damage and failure in these material systems. With polymer matrix fiber composites and nanocomposites it becomes essential to include even the atomic length scale, where the resin-hardener-nanofiller molecules interact, in the multiscale modeling framework. Additionally, sources of variability are also critical to be included in these models due to the important role of uncertainty in advance composite behavior. Such a methodology should be able to describe length scale dependent mechanisms in a computationally efficient manner for the analysis of practical composite structures.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
ContributorsRai, Ashwin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Fard, Masoud Yekani (Committee member) / Arizona State University (Publisher)
Created2018
Description
Dealloying, the selective electrochemical dissolution of an active component from an alloy, often results in nanoscale bi-continuous solid/void morphologies. These structures are attracting attention for a wide range of applications including catalysis, sensing and actuation. The evolution of these nanoporous structures has been widely studied for the case at low homologous temperature, TH, such as in Ag-Au, Cu-Au, Cu-Pt, etc. Since at low TH the solid-state mobility of the components is of order 10-30 cm2s-1 or less, percolation dissolution is the only mechanism available to support dealloying over technologically relevant time scales. Without the necessity of solid-state mass transport, percolation dissolution involves sharp transitions based on two key features, the parting limit and critical potential.
Dealloying under conditions of high TH, (or high intrinsic diffusivity of the more electrochemically reactive component) is considerably more complicated than at low TH. Since solid-state mass transport is available to support this process, a rich set of morphologies, including negative or void dendrites, Kirkendall voids and bi-continuous porous structures, can evolve. In order to study dealloying at high TH we have examined the behavior of Li-Sn and Li-Pb alloys. The intrinsic diffusivities of Li were measured in these alloys using electrochemical titration and time of flight measurements. Morphology evolution was studied with varying alloy composition, host dimension and imposed electrochemical conditions. Owing to diffusive transport, there is no parting limit for dealloying, however, there is a compositional threshold (pPD) as well as a critical potential for the operation of percolation dissolution and the formation of bi-continuous structures. Negative or void dendrite morphologies evolve at compositions below pPD and at large values of the applied electrochemical potential when the rate of dealloying is limited by solid-state mass transport. This process is isomorphic to dendrite formation in electrodeposition. Kirkendall voiding morphologies evolve below the critical potential over the entire range of alloy compositions.
We summarize our results by introducing dealloying morphology diagrams that we use to graphically illustrate the electrochemical conditions resulting in various morphologies that can form under conditions of low and high TH.
Dealloying under conditions of high TH, (or high intrinsic diffusivity of the more electrochemically reactive component) is considerably more complicated than at low TH. Since solid-state mass transport is available to support this process, a rich set of morphologies, including negative or void dendrites, Kirkendall voids and bi-continuous porous structures, can evolve. In order to study dealloying at high TH we have examined the behavior of Li-Sn and Li-Pb alloys. The intrinsic diffusivities of Li were measured in these alloys using electrochemical titration and time of flight measurements. Morphology evolution was studied with varying alloy composition, host dimension and imposed electrochemical conditions. Owing to diffusive transport, there is no parting limit for dealloying, however, there is a compositional threshold (pPD) as well as a critical potential for the operation of percolation dissolution and the formation of bi-continuous structures. Negative or void dendrite morphologies evolve at compositions below pPD and at large values of the applied electrochemical potential when the rate of dealloying is limited by solid-state mass transport. This process is isomorphic to dendrite formation in electrodeposition. Kirkendall voiding morphologies evolve below the critical potential over the entire range of alloy compositions.
We summarize our results by introducing dealloying morphology diagrams that we use to graphically illustrate the electrochemical conditions resulting in various morphologies that can form under conditions of low and high TH.
ContributorsGeng, Ke (Author) / Sieradzki, Karl (Thesis advisor) / Crozier, Peter (Committee member) / Chan, Candace (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2017