Matching Items (118)
Description
High-entropy alloys (HEAs) is a new class of materials which have been studied heavily due to their special mechanical properties. HEAs refers to alloys with multiple equimolar or nearly equimolar elements. HEAs show exceptional and attractive properties currently absent from conventional alloys, which make them the center of intense investigation. HEAs obtain their properties from four core effects that they exhibit and most of the work on them have been dedicated to study their mechanical properties. In contrast, little or no research have gone into studying the functional or even thermal properties of HEAs. Some HEAs have also shown exceptional or very high melting points. According to the definition of HEAs, Si-Ge-Sn alloys with equal or comparable concentrations of the three group IV elements belong to the category of HEAs. Thus, the equimolar components of Si-Ge-Sn alloys probably allow their atomic structures to display the same fundamental effects of metallic HEAs. The experimental fabrication of such alloys has been proven to be very difficult, which is mainly due to differences between the properties of their constituent elements, as indicated from their binary phase diagrams. However, previous computational studies have shown that SiGeSn HEAs have some very interesting properties, such as high electrical conductivity, low thermal conductivity and semiconducting properties. In this work, going for a complete characterization of the SiGeSn HEA properties, the melting point of this alloy is studied using classical molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The aim is to investigate the effects of high Sn content in this alloy on the melting point compared with the traditional SiGe alloys. Classical MD simulations results strongly indicates that none of the available empirical potentials is able to predict accurate or reasonable melting points for SiGeSn HEAs and most of its subsystems. DFT calculations results show that SiGeSn HEA have a melting point which represent the mean value of its constituent elements and that no special deviations are found. This work contributes to the study of SiGeSn HEA properties, which can serve as guidance before the successful experimental fabrication of this alloy.
ContributorsAlqaisi, Ahmad Madhat Odeh (Author) / Hong, Qi-Jun (Thesis advisor) / Zhuang, Houlong (Thesis advisor) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2023
Description
This paper presents a comprehensive review of current advances and challenges in the field of bone tissue engineering. A systematic review of the literature was conducted to identify recent developments in biomaterials, scaffold design, cell sources, and growth factors for bone tissue engineering applications. Based on this review, an experimental proposal is presented for the development of porous composite biomaterials that may enhance bone regeneration, which consist of hybrid amyloid/spidroin fibers combined with a bioactive ceramic matrix. An iterative design process of modeling and simulation, production, and characterization of both the fibers and the composite material is proposed. A modeling and simulation approach is also presented for unidirectional fiber composite biomaterials using 2-point correlation functions, finite element simulations, and machine learning. This approach was demonstrated to enable the efficient and accurate prediction of the effective Young’s modulus of candidate composite biomaterials, which can inform the design of optimized materials for bone tissue engineering applications. The proposed experimental and simulation approaches have the potential to address current challenges and lead to the development of novel composite biomaterials that can augment the current technologies in the field of bone tissue engineering.
ContributorsThornton, Bryce (Author) / Hartwell, Leland (Thesis director) / Jiao, Yang (Committee member) / Susarla, Sandhya (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor)
Created2023-05
Description
Phase-field (PF) models are one of the most powerful tools to simulate microstructural evolution in metallic materials, polymers, and ceramics. However, existing PF approaches rely on rigorous mathematical model development, sophisticated numerical schemes, and high-performance computing for accuracy. Although recently developed surrogate microstructure models employ deep-learning techniques and reconstruction of microstructures from lower-dimensional data, their accuracy is fairly limited as spatio-temporal information is lost in the pursuit of dimensional reduction. Given these limitations, a novel data-driven emulator (DDE) for extrapolation prediction of microstructural evolution is presented, which combines an image-based convolutional and recurrent neural network (CRNN) with tensor decomposition, while leveraging previously obtained PF datasets for training. To assess the robustness of DDE, the emulation sequence and the scaling behavior with phase-field simulations for several noisy initial states are compared. In conclusion, the effectiveness of the microstructure emulation technique is explored in the context of accelerating runtime, along with an emphasis on its trade-off with accuracy.Meanwhile, an interpolation DDE has also been tested, which is based on obtaining
a low-dimensional representation of the microstructures via tensor decomposition and subsequently predicting the microstructure evolution in the low-dimensional space using Gaussian process regression (GPR). Once the microstructure predictions are obtained in the low-dimensional space, a hybrid input-output phase retrieval algorithm will be employed to reconstruct the microstructures. As proof of concept, the results on microstructure prediction for spinodal decomposition are presented, although the method itself is agnostic of the material parameters. Results show that GPR-based DDE model are able to predict microstructure evolution sequences that closely resemble the true microstructures (average normalized mean square of 6.78 × 10−7) at time scales half of that employed in obtaining training data. This data-driven
microstructure emulator opens new avenues to predict the microstructural evolution by leveraging phase-field simulations and physical experimentation where the time resolution is often quite large due to limited resources and physical constraints, such as the phase coarsening experiments previously performed in microgravity.
Future work will also be discussed and demonstrate the intended utilization of these two approaches for 3D microstructure prediction through their combined application.
ContributorsWu, Peichen (Author) / Ankit, Kumar (Thesis advisor) / Iquebal, Ashif (Committee member) / Jiao, Yang (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2024
Description
Weevils are among the most diverse and evolutionarily successful animal lineages on Earth. Their success is driven in part by a structure called the rostrum, which gives weevil heads a characteristic "snout-like" appearance. Nut weevils in the genus Curculio use the rostrum to drill holes into developing fruits and nuts, wherein they deposit their eggs. During oviposition this exceedingly slender structure is bent into a straightened configuration - in some species up to 90° - but does not suffer any damage during this process. The performance of the snout is explained in terms of cuticle biomechanics and rostral curvature, as presented in a series of four interconnected studies. First, a micromechanical constitutive model of the cuticle is defined to predict and reconstruct the mechanical behavior of each region in the exoskeleton. Second, the effect of increased endocuticle thickness on the stiffness and fracture strength of the rostrum is assessed using force-controlled tensile testing. In the third chapter, these studies are integrated into finite element models of the snout, demonstrating that the Curculio rostrum is only able to withstand repeated, extreme bending because of
modifications to the composite structure of the cuticle in the rostral apex. Finally, interspecific differences in the differential geometry of the snout are characterized to elucidate the role of biomechanical constraint in the evolution of rostral morphology for both males and females. Together these studies highlight the significance of cuticle biomechanics - heretofore unconsidered by others - as a source of constraint on the evolution of the rostrum and the mechanobiology of the genus Curculio.
modifications to the composite structure of the cuticle in the rostral apex. Finally, interspecific differences in the differential geometry of the snout are characterized to elucidate the role of biomechanical constraint in the evolution of rostral morphology for both males and females. Together these studies highlight the significance of cuticle biomechanics - heretofore unconsidered by others - as a source of constraint on the evolution of the rostrum and the mechanobiology of the genus Curculio.
ContributorsJansen, Michael Andrew (Author) / Franz, Nico M (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Harrison, Jon (Committee member) / Martins, Emilia (Committee member) / Arizona State University (Publisher)
Created2009
Description
Being a remarkably versatile and inexpensive building material, concrete has found tremendous use in development of modern infrastructure and is the most widely used material in the world. Extensive research in the field of concrete has led to the development of a wide array of concretes with applications ranging from building of skyscrapers to paving of highways. These varied applications require special cementitious composites which can satisfy the demand for enhanced functionalities such as high strength, high durability and improved thermal characteristics among others.
The current study focuses on the fundamental understanding of such functional composites, from their microstructural design to macro-scale application. More specifically, this study investigates three different categories of functional cementitious composites. First, it discusses the differences between cementitious systems containing interground and blended limestone with and without alumina. The interground systems are found to outperform the blended systems due to differential grinding of limestone. A novel approach to deduce the particle size distribution of limestone and cement in the interground systems is proposed. Secondly, the study delves into the realm of ultra-high performance concrete, a novel material which possesses extremely high compressive-, tensile- and flexural-strength and service life as compared to regular concrete. The study presents a novel first principles-based paradigm to design economical ultra-high performance concretes using locally available materials. In the final part, the study addresses the thermal benefits of a novel type of concrete containing phase change materials. A software package was designed to perform numerical simulations to analyze temperature profiles and thermal stresses in concrete structures containing PCMs.
The design of these materials is accompanied by material characterization of cementitious binders. This has been accomplished using techniques that involve measurement of heat evolution (isothermal calorimetry), determination and quantification of reaction products (thermo-gravimetric analysis, x-ray diffraction, micro-indentation, scanning electron microscopy, energy-dispersive x-ray spectroscopy) and evaluation of pore-size distribution (mercury intrusion porosimetry). In addition, macro-scale testing has been carried out to determine compression, flexure and durability response. Numerical simulations have been carried out to understand hydration of cementitious composites, determine optimum particle packing and determine the thermal performance of these composites.
The current study focuses on the fundamental understanding of such functional composites, from their microstructural design to macro-scale application. More specifically, this study investigates three different categories of functional cementitious composites. First, it discusses the differences between cementitious systems containing interground and blended limestone with and without alumina. The interground systems are found to outperform the blended systems due to differential grinding of limestone. A novel approach to deduce the particle size distribution of limestone and cement in the interground systems is proposed. Secondly, the study delves into the realm of ultra-high performance concrete, a novel material which possesses extremely high compressive-, tensile- and flexural-strength and service life as compared to regular concrete. The study presents a novel first principles-based paradigm to design economical ultra-high performance concretes using locally available materials. In the final part, the study addresses the thermal benefits of a novel type of concrete containing phase change materials. A software package was designed to perform numerical simulations to analyze temperature profiles and thermal stresses in concrete structures containing PCMs.
The design of these materials is accompanied by material characterization of cementitious binders. This has been accomplished using techniques that involve measurement of heat evolution (isothermal calorimetry), determination and quantification of reaction products (thermo-gravimetric analysis, x-ray diffraction, micro-indentation, scanning electron microscopy, energy-dispersive x-ray spectroscopy) and evaluation of pore-size distribution (mercury intrusion porosimetry). In addition, macro-scale testing has been carried out to determine compression, flexure and durability response. Numerical simulations have been carried out to understand hydration of cementitious composites, determine optimum particle packing and determine the thermal performance of these composites.
ContributorsArora, Aashay (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Chawla, Nikhilesh (Committee member) / Hoover, Christian G (Committee member) / Arizona State University (Publisher)
Created2018
Description
Additive manufacturing (AM) describes an array of methods used to create a 3D object layer by layer. The increasing popularity of AM in the past decade has been due to its demonstrated potential to increase design flexibility, produce rapid prototypes, and decrease material waste. Temporary supports are an inconvenient necessity in many metal AM parts. These sacrificial structures are used to fabricate large overhangs, anchor the part to the build substrate, and provide a heat pathway to avoid warping. Polymers AM has addressed this issue by using support material that is soluble in an electrolyte that the base material is not. In contrast, metals AM has traditionally approached support removal using time consuming, costly methods such as electrical discharge machining or a dremel.
This work introduces dissolvable supports to single- and multi-material metals AM. The multi-material approach uses material choice to design a functionally graded material where corrosion is the functionality being varied. The single-material approach is the primary focus of this thesis, leveraging already common post-print heat treatments to locally alter the microstructure near the surface. By including a sensitizing agent in the ageing heat treatment, carbon is diffused into the part decreasing the corrosion resistance to a depth equal to at least half the support thickness. In a properly chosen electrolyte, this layer is easily chemically, or electrochemically removed. Stainless steel 316 (SS316) and Inconel 718 are both investigated to study this process using two popular alloys. The microstructure evolution and corrosion properties are investigated for both. For SS316, the effect of applied electrochemical potential is investigated to describe the varying corrosion phenomena induced, and the effect of potential choice on resultant roughness. In summary, a new approach to remove supports from metal AM parts is introduced to decrease costs and further the field of metals AM by expanding the design space.
This work introduces dissolvable supports to single- and multi-material metals AM. The multi-material approach uses material choice to design a functionally graded material where corrosion is the functionality being varied. The single-material approach is the primary focus of this thesis, leveraging already common post-print heat treatments to locally alter the microstructure near the surface. By including a sensitizing agent in the ageing heat treatment, carbon is diffused into the part decreasing the corrosion resistance to a depth equal to at least half the support thickness. In a properly chosen electrolyte, this layer is easily chemically, or electrochemically removed. Stainless steel 316 (SS316) and Inconel 718 are both investigated to study this process using two popular alloys. The microstructure evolution and corrosion properties are investigated for both. For SS316, the effect of applied electrochemical potential is investigated to describe the varying corrosion phenomena induced, and the effect of potential choice on resultant roughness. In summary, a new approach to remove supports from metal AM parts is introduced to decrease costs and further the field of metals AM by expanding the design space.
ContributorsLefky, Christopher (Author) / Hildreth, Owen (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Azeredo, Bruno (Committee member) / Rykaczewski, Konrad (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Fatigue is a degradation process of materials that would lead to failure when materials are subjected to cyclic loadings. During past centuries, various of approaches have been proposed and utilized to help researchers understand the underlying theories of fatigue behavior of materials, as well as design engineering structures so that catastrophic disasters that arise from fatigue failure could be avoided. The stress-life approach is the most classical way that academia applies to analyze fatigue data, which correlates the fatigue lifetime with stress amplitudes during cyclic loadings. Fracture mechanics approach is another well-established way, by which people regard the cyclic stress intensity factor as the driving force during fatigue crack nucleation and propagation, and numerous models (such as the well-known Paris’ law) are developed by researchers.
The significant drawback of currently widely-used fatigue analysis approaches, nevertheless, is that they are all cycle-based, limiting researchers from digging into sub-cycle regime and acquiring real-time fatigue behavior data. The missing of such data further impedes academia from validating hypotheses that are related to real-time observations of fatigue crack nucleation and growth, thus the existence of various phenomena, such as crack closure, remains controversial.
In this thesis, both classical stress-life approach and fracture-mechanics-based approach are utilized to study the fatigue behavior of alloys. Distinctive material characterization instruments are harnessed to help collect and interpret key data during fatigue crack growth. Specifically, an investigation on the sub-cycle fatigue crack growth behavior is enabled by in-situ SEM mechanical testing, and a non-uniform growth mechanism within one loading cycle is confirmed by direct observation as well as image interpretation. Predictions based on proposed experimental procedure and observations show good match with cycle-based data from references, which indicates the credibility of proposed methodology and model, as well as their capability of being applied to a wide range of materials.
The significant drawback of currently widely-used fatigue analysis approaches, nevertheless, is that they are all cycle-based, limiting researchers from digging into sub-cycle regime and acquiring real-time fatigue behavior data. The missing of such data further impedes academia from validating hypotheses that are related to real-time observations of fatigue crack nucleation and growth, thus the existence of various phenomena, such as crack closure, remains controversial.
In this thesis, both classical stress-life approach and fracture-mechanics-based approach are utilized to study the fatigue behavior of alloys. Distinctive material characterization instruments are harnessed to help collect and interpret key data during fatigue crack growth. Specifically, an investigation on the sub-cycle fatigue crack growth behavior is enabled by in-situ SEM mechanical testing, and a non-uniform growth mechanism within one loading cycle is confirmed by direct observation as well as image interpretation. Predictions based on proposed experimental procedure and observations show good match with cycle-based data from references, which indicates the credibility of proposed methodology and model, as well as their capability of being applied to a wide range of materials.
ContributorsLiu, Siying (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Nanolaminate materials are layered composites with layer thickness ≤ 100 nm. They exhibit unique properties due to their small length scale, the presence of a high number of interfaces and the effect of imposed constraint. This thesis focuses on the mechanical behavior of Al/SiC nanolaminates. The high strength of ceramics combined with the ductility of Al makes this combination desirable. Al/SiC nanolaminates were synthesized through magnetron sputtering and have an overall thickness of ~ 20 μm which limits the characterization techniques to microscale testing methods. A large amount of work has already been done towards evaluating their mechanical properties under indentation loading and micropillar compression. The effects of temperature, orientation and layer thickness have been well established. Al/SiC nanolaminates exhibited a flaw dependent deformation, anisotropy with respect to loading direction and strengthening due to imposed constraint. However, the mechanical behavior of nanolaminates under tension and fatigue loading has not yet been studied which is critical for obtaining a complete understanding of their deformation behavior. This thesis fills this gap and presents experiments which were conducted to gain an insight into the behavior of nanolaminates under tensile and cyclic loading. The effect of layer thickness, tension-compression asymmetry and effect of a wavy microstructure on mechanical response have been presented. Further, results on in situ micropillar compression using lab-based X-ray microscope through novel experimental design are also presented. This was the first time when a resolution of 50 nms was achieved during in situ micropillar compression in a lab-based setup. Pores present in the microstructure were characterized in 3D and sites of damage initiation were correlated with the channel of pores present in the microstructure.
The understanding of these deformation mechanisms paved way for the development of co-sputtered Al/SiC composites. For these composites, Al and SiC were sputtered together in a layer. The effect of change in the atomic fraction of SiC on the microstructure and mechanical properties were evaluated. Extensive microstructural characterization was performed at the nanoscale level and Al nanocrystalline aggregates were observed dispersed in an amorphous matrix. The modulus and hardness of co- sputtered composites were much higher than their traditional counterparts owing to denser atomic packing and the absence of synthesis induced defects such as pores and columnar boundaries.
The understanding of these deformation mechanisms paved way for the development of co-sputtered Al/SiC composites. For these composites, Al and SiC were sputtered together in a layer. The effect of change in the atomic fraction of SiC on the microstructure and mechanical properties were evaluated. Extensive microstructural characterization was performed at the nanoscale level and Al nanocrystalline aggregates were observed dispersed in an amorphous matrix. The modulus and hardness of co- sputtered composites were much higher than their traditional counterparts owing to denser atomic packing and the absence of synthesis induced defects such as pores and columnar boundaries.
ContributorsSingh, Somya (Author) / Chawla, Nikhilesh (Thesis advisor) / Neithalath, Narayanan (Committee member) / Jiao, Yang (Committee member) / Mara, Nathan (Committee member) / Arizona State University (Publisher)
Created2018
Description
With the growth of global population, the demand for sustainable infrastructure is significantly increasing. Substructures with appropriate materials are required to be built in or above soil that can support the massive volume of construction demand. However, increased structural requirements often require ground improvement to increase the soil capacity. Moreover, certain soils are prone to liquefaction during an earthquake, which results in significant structural damage and loss of lives. While various soil treatment methods have been developed in the past to improve the soil’s load carrying ability, most of these traditional treatment methods have been found either hazardous and may cause irreversible damage to natural environment, or too disruptive to use beneath or adjacent to existing structures. Thus, alternative techniques are required to provide a more natural and sustainable solution. Biomediated methods of strengthening soil through mineral precipitation, in particular through microbially induced carbonate precipitation (MICP), have recently emerged as a promising means of soil improvement. In MICP, the precipitation of carbonate (usually in the form of calcium carbonate) is mediated by microorganisms and the process is referred to as biomineralization. The precipitated carbonate coats soil particles, precipitates in the voids, and bridges between soil particles, thereby improving the mechanical properties (e.g., strength, stiffness, and dilatancy). Although it has been reported that the soil’s mechanical properties can be extensively enhanced through MICP, the micro-scale mechanisms that influence the macro-scale constitutive response remain to be clearly explained.
The utilization of alternative techniques such as MICP requires an in-depth understanding of the particle-scale contact mechanisms and the ability to predict the improvement in soil properties resulting from calcite precipitation. For this purpose, the discrete element method (DEM), which is extensively used to investigate granular materials, is adopted in this dissertation. Three-dimensional discrete element method (DEM) based numerical models are developed to simulate the response of bio-cemented sand under static and dynamic loading conditions and the micro-scale mechanisms of MICP are numerically investigated. Special focus is paid to the understanding of the particle scale mechanisms that are dominant in the common laboratory scale experiments including undrained and drained triaxial compression when calcite bridges are present in the soil, that enhances its load capacity. The mechanisms behind improvement of liquefaction resistance in cemented sands are also elucidated through the use of DEM. The thesis thus aims to provide the fundamental link that is important in ensuring proper material design for granular materials to enhance their mechanical performance.
The utilization of alternative techniques such as MICP requires an in-depth understanding of the particle-scale contact mechanisms and the ability to predict the improvement in soil properties resulting from calcite precipitation. For this purpose, the discrete element method (DEM), which is extensively used to investigate granular materials, is adopted in this dissertation. Three-dimensional discrete element method (DEM) based numerical models are developed to simulate the response of bio-cemented sand under static and dynamic loading conditions and the micro-scale mechanisms of MICP are numerically investigated. Special focus is paid to the understanding of the particle scale mechanisms that are dominant in the common laboratory scale experiments including undrained and drained triaxial compression when calcite bridges are present in the soil, that enhances its load capacity. The mechanisms behind improvement of liquefaction resistance in cemented sands are also elucidated through the use of DEM. The thesis thus aims to provide the fundamental link that is important in ensuring proper material design for granular materials to enhance their mechanical performance.
ContributorsYang, Pu (Author) / Neithalath, Narayanan (Thesis advisor) / Kavazanjian, Edward (Committee member) / Rajan, S.D. (Committee member) / Mobasher, Barzin (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2018