Matching Items (118)
Description
With the abundance of increasingly large datasets, the ability to predict the phase of high-entropy alloys (HEAs) based solely on elemental composition could become a reliable tool for the discovery of new HEAs. However, as the amount of data expands so does the computational time and resources required to train predictive classical machine learning models. Quantum computers, which use quantum bits (qubits), could be the solution to overcoming these demands. Their ability to use quantum superposition and interference to perform calculations could be the key to handling large amounts of data. In this work, a hybrid quantum-classical machine learning algorithm is implemented on both quantum simulators and quantum processors to perform the supervised machine learning task. Their feasibility as a future tool for HEA discovery is evaluated based on the algorithm’s performance. An artificial neural network (ANN), run by classical computers, is also trained on the same data for performance comparison. The accuracy of the quantum-classical model was found to be comparable to the accuracy achieved by the classical ANN with a slight decrease in accuracy when ran on quantum hardware due to qubit susceptibility to decoherence. Future developments in the applied quantum machine learning method are discussed.
ContributorsBrown, Payden Lance (Author) / Zhuang, Houlong (Thesis advisor) / Ankit, Kumar (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Computational materials is a field that utilizes modeling, simulations, and technology to study how materials behave. This honors thesis is a presentation discussing computational materials, our study of packing theory using the Monte Carlo (MC), and how our research can be related to real materials we use.
ContributorsVidallon, Justine Ilyssa (Author) / Jiao, Yang (Thesis director) / Zhuang, Houlong (Committee member) / Barrett, The Honors College (Contributor) / Materials Science and Engineering Program (Contributor)
Created2023-05
Description
Cellular metamaterials arouse broad scientific interests due to the combination of host material and structure together to achieve a wide range of physical properties rarely found in nature. Stochastic foam as one subset has been considered as a competitive candidate for versatile applications including heat exchangers, battery electrodes, automotive, catalyst devices, magnetic shielding, etc. For the engineering of the cellular foam architectures, closed-form models that can be used to predict the mechanical and thermal properties of foams are highly desired especially for the recently developed ultralight weight shellular architectures. Herein, for the first time, a novel packing three-dimensional (3D) hollow pentagonal dodecahedron (HPD) model is proposed to simulate the cellular architecture with hollow struts. An electrochemical deposition process is utilized to manufacture the metallic hollow foam architecture. Mechanical and thermal testing of the as-manufactured foams are carried out to compare with the HPD model. Timoshenko beam theory is utilized to verify and explain the derived power coefficient relation. Our HPD model is proved to accurately capture both the topology and the physical properties of hollow stochastic foam. Understanding how the novel HPD model packing helps break the conventional impression that 3D pentagonal topology cannot fulfill the space as a representative volume element. Moreover, the developed HPD model can predict the mechanical and thermal properties of the manufactured hollow metallic foams and elucidating of how the inevitable manufacturing defects affect the physical properties of the hollow metallic foams. Despite of the macro-scale stochastic foam architecture, nano gradient gyroid lattices are studied using Molecular Dynamics (MD) simulation. The simulation result reveals that, unlike homogeneous architecture, gradient gyroid not only shows novel layer-by-layer deformation behavior, but also processes significantly better energy absorption ability. The deformation behavior and energy absorption are predictable and designable, which demonstrate its highly programmable potential.
ContributorsDai, Rui (Author) / Nian, Qiong (Thesis advisor) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Liu, Yongming (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2021
Description
Ultra-fast 2D/3D material microstructure reconstruction and quantitative structure-property mapping are crucial components of integrated computational material engineering (ICME). It is particularly challenging for modeling random heterogeneous materials such as alloys, composites, polymers, porous media, and granular matters, which exhibit strong randomness and variations of their material properties due to the hierarchical uncertainties associated with their complex microstructure at different length scales. Such uncertainties also exist in disordered hyperuniform systems that are statistically isotropic and possess no Bragg peaks like liquids and glasses, yet they suppress large-scale density fluctuations in a similar manner as in perfect crystals. The unique hyperuniform long-range order in these systems endow them with nearly optimal transport, electronic and mechanical properties. The concept of hyperuniformity was originally introduced for many-particle systems and has subsequently been generalized to heterogeneous materials such as porous media, composites, polymers, and biological tissues for unconventional property discovery. An explicit mixture random field (MRF) model is proposed to characterize and reconstruct multi-phase stochastic material property and microstructure simultaneously, where no additional tuning step nor iteration is needed compared with other stochastic optimization approaches such as the simulated annealing. The proposed method is shown to have ultra-high computational efficiency and only requires minimal imaging and property input data. Considering microscale uncertainties, the material reliability will face the challenge of high dimensionality. To deal with the so-called “curse of dimensionality”, efficient material reliability analysis methods are developed. Then, the explicit hierarchical uncertainty quantification model and efficient material reliability solvers are applied to reliability-based topology optimization to pursue the lightweight under reliability constraint defined based on structural mechanical responses. Efficient and accurate methods for high-resolution microstructure and hyperuniform microstructure reconstruction, high-dimensional material reliability analysis, and reliability-based topology optimization are developed. The proposed framework can be readily incorporated into ICME for probabilistic analysis, discovery of novel disordered hyperuniform materials, material design and optimization.
ContributorsGao, Yi (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Ren, Yi (Committee member) / Pan, Rong (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2021
Description
Damage and failure of advanced composite materials and structures are often manifestations of nonlinear deformation that involve multiple mechanisms and their interactions at the constituent length scale. The presence and interactions of inelastic microscale constituents strongly influence the macroscopic damage anisotropy and useful residual life. The mechano-chemical interactions between constituents at the atomistic length scale play a more critical role with nanoengineered composites. Therefore, it is desirable to link composite behavior to specific microscopic constituent properties explicitly and lower length scale features using high-fidelity multiscale modeling techniques.In the research presented in this dissertation, an atomistically-informed multiscale modeling framework is developed to investigate damage evolution and failure in composites with radially-grown carbon nanotube (CNT) architecture. A continuum damage mechanics (CDM) model for the radially-grown CNT interphase region is developed with evolution equations derived using atomistic simulations. The developed model is integrated within a high-fidelity generalized method of cells (HFGMC) micromechanics theory and is used to parametrically investigate the influence of various input micro and nanoscale parameters on the mechanical properties, such as elastic stiffness, strength, and toughness. In addition, the inter-fiber stresses and the onset of damage in the presence of the interphase region are investigated to better understand the energy dissipation mechanisms that attribute to the enhancement in the macroscopic out-of-plane strength and toughness. Note that the HFGMC theory relies heavily on the description of microscale features and requires many internal variables, leading to high computational costs. Therefore, a novel reduced-order model (ROM) is also developed to surrogate full-field nonlinear HFGMC simulations and decrease the computational time and memory requirements of concurrent multiscale simulations significantly.
The accurate prediction of composite sandwich materials' thermal stability and durability remains a challenge due to the variability of thermal-related material coefficients at different temperatures and the extensive use of bonded fittings. Consequently, the dissertation also investigates the thermomechanical performance of a complex composite sandwich space structure subject to thermal cycling. Computational finite element (FE) simulations are used to investigate the intrinsic failure mechanisms and damage precursors in honeycomb core composite sandwich structures with adhesively bonded fittings.
ContributorsVenkatesan, Karthik Rajan (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Yekani Fard, Masoud (Committee member) / Stoumbos, Tom (Committee member) / Arizona State University (Publisher)
Created2021
Description
Atmospheric water extraction (AWE) is an emerging technology to tackle water resource shortage challenges. One such approach to provide fresh water utilizes stimuli-responsive hydrogel-based desiccants to capture the moisture from the air and release it into the liquid form. Typical gel desiccants are composed of a hygroscopic agent for capturing and a hydrophilic gel matrix for storage. The desorption process can be completed by elevating the temperature above the upper or lower critical solution temperature point to initiate the volume phase transition of either thermo-responsive or photothermal types. This thesis focuses on investigating the structural effect of hydrogels on moisture uptake. Firstly, the main matrix of gel desiccant, poly(N-isopropylacrylamide) hydrogel, was optimized via tuning synthesis temperature and initial monomer concentration. Secondly, a series of hydrogel-based desiccants consisting of a hygroscopic material, vinyl imidazole, and optimized poly(N-isopropylacrylamide) gel matrix were synthesized with different network structures. The moisture uptake result showed that the gel desiccant with an interpenetrating polymeric network (IPN) resulted in the best-performing moisture capturing. The gel desiccant with the best performance will be used as a primary structural unit to evaluate the feasibility of developing a light-responsive gel desiccant to materialize light-trigger moisture desorption for AWE technology in the future.
ContributorsZhao, Xingbang (Author) / Dai, Lenore (Thesis advisor) / Westerhoff, Paul (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
Glasses have many applications such as containers, substrates of displays, high strength fibers and portable electronic display panels. Their excellent mechanical properties such as high hardness, good forming ability and scratch resistance make glasses ideal for these applications. Many factors affect the selection of one glass over another for a given purpose such as cost, ingredients, scalability of manufacturing, etc. Typically, silicate based glasses are often selected because they satisfy most of the selection criteria. However, with the recent abundant use of these glasses in touch-based applications, understanding their abilities to dissipate energy due to surface contact loads has become increasingly desirable. The most common silicate glasses worldwide are glassy silica and soda lime. Calcium aluminosilicates are also gaining popularity due to their importance as substrates for display screens in electronic devices. The surface energy dissipation and strength of these glasses are based on several factors, but predominantly rely on ingredient composition and the so-called Indentation Size Effect (ISE), where the strength depends on the maximum surface force. Both the composition and ISE alter the strength and favored energy dissipation mechanisms of the glass. Unlocking the contribution of these mechanisms and elucidating their dependence on composition and force is the underlining goal of this thesis.Prior to cracking, silicate glasses can inelastically deform by shear and densification. However, the link between the mechanical properties, strength, glass structure and maximum force and the propensity by which either of these mechanisms are favored still remains unclear. In this study, the first aim is to elucidate the causes of the ISE and
i
explore the relationships between the ISE and the dissipation mechanisms, and identify what feature(s) of the glass can be used to infer their behavior. All glasses have shown a strong link between the ISE and shear flow and densification. Second, the link between composition and the dissipation mechanisms will be elucidated. This is accomplished by performing indentation tests coupled with an annealing method to independently quantify the amount of volume associated with each dissipation mechanism and elucidate relationships with ingredients and structure of the glasses. Some conclusions will then be presented that link all these behaviors together.
ContributorsKazembeyki, Maryam (Author) / Hoover, Christian G (Thesis advisor) / Rajan, Subramaniam (Committee member) / Neithalath, Narayanan (Committee member) / Chawla, Nikhilesh (Committee member) / Perreault, Francois (Committee member) / Arizona State University (Publisher)
Created2021
Description
In this dissertation, two types of passive air freshener products from Henkel, the wick-based air freshener and gel-based air freshener, are studied for their wicking mechanisms and evaporation performances.The fibrous pad of the wick-based air freshener is a porous medium that absorbs fragrance by capillary force and releases the fragrance into the ambient air. To investigate the wicking process, a two-dimensional multiphase flow numerical model using COMSOL Multiphysics is built. Saturation and liquid pressure inside the pad are solved. Comparison between the simulation results and experiments shows that evaporation occurs simultaneously with the wicking process. The evaporation performance on the surface of the wicking pad is analyzed based on the kinetic theory, from which the mass flow rate of molecules passing the interface of each pore of the porous medium is obtained. A 3D model coupling the evaporation model and dynamic wicking on the evaporation pad is built to simulate the entire performance of the air freshener to the environment for a long period of time. Diffusion and natural convection effects are included in the simulation. The simulation results match well with the experiments for both the air fresheners placed in a chamber and in the absent of a chamber, the latter of which is subject to indoor airflow.
The gel-based air freshener can be constructed as a porous medium in which the solid network of particles spans the volume of the fragrance liquid. To predict the evaporation performance of the gel, two approaches are tested for gel samples in hemispheric shape. The first approach is the sessile drop model commonly used for the drying process of a pure liquid droplet. It can be used to estimate the weight loss rate and time duration of the evaporation. Another approach is to simulate the concentration profile outside the gel and estimate the evaporation rate from the surface of the gel using the kinetic theory. The evaporation area is updated based on the change of pore size. A 3D simulation using the same analysis is further applied to the cylindrical gel sample. The simulation results match the experimental data well.
ContributorsYuan, Jing (Author) / Chen, Kangping (Thesis advisor) / Herrmann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Wang, Liping (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
In the age of 5th and upcoming 6th generation fighter aircraft one key proponent of these impressive machines is the inclusion of stealth. This inclusion is demonstrated by thoughtful design pertaining to the shape of the aircraft and rigorous material selection. Both criteria aim to minimize the radar cross section of these aircraft over a wide bandwidth of frequencies corresponding to an ever-evolving field of radar technology. Stealth is both an offensive and defensive capability meaning that service men and women depend on this feature to carry out their missions, and to return home safely. The goal of this paper is to introduce a novel method to designing disordered two-phase composites with desired electromagnetic properties. This task is accomplished by employing the spatial point correlation function, specifically at the two-point level. Effective at describing the dispersion of phases within a two-phase system, the two-point correlation function serves as a statistical function that becomes a realizable target for heterogeneous composites. Simulated annealing is exercised to reconstruct two-phase composite microstructures that initially do not match their target function, followed by two separate experiments aimed at studying the impact of the provided inputs on its outcome. Once conditions for reconstructing highly accurate microstructures are identified, modifications are made to the target function to extract and compare dielectric constants associated with each microstructure. Both the real and imaginary components, which respectively affect wave propagation and attenuation, of the dielectric constants are plotted to illustrate their behavior with increasing wavenumber. Conclusions suggest that favorable values of the complex dielectric constant can be reverse-engineered via careful consideration of the two-point correlation function. Subsequently, corresponding microstructures of the composite can be simulated and then produced through 3-D printing for testing and practical applications.
ContributorsPlantz, Alex Chadewick (Author) / Jiao, Yang (Thesis advisor) / Zhuang, Houlong (Committee member) / Yang, Sui (Committee member) / Arizona State University (Publisher)
Created2024
Description
The design of energy absorbing structures is driven by application specific requirements like the amount of energy to be absorbed, maximum transmitted stress that is permissible, stroke length, and available enclosing space. Cellular structures like foams are commonly leveraged in nature for energy absorption and have also found use in engineering applications. With the possibility of manufacturing complex cellular shapes using additive manufacturing technologies, there is an opportunity to explore new topologies that improve energy absorption performance. This thesis aims to systematically understand the relationships between four key elements: (i) unit cell topology, (ii) material composition, (iii) relative density, and (iv) fields; and energy absorption behavior, and then leverage this understanding to develop, implement and validate a methodology to design the ideal cellular structure energy absorber. After a review of the literature in the domain of additively manufactured cellular materials for energy absorption, results from quasi-static compression of six cellular structures (hexagonal honeycomb, auxetic and Voronoi lattice, and diamond, Gyroid, and Schwarz-P) manufactured out of AlSi10Mg and Nylon-12. These cellular structures were compared to each other in the context of four design-relevant metrics to understand the influence of cell design on the deformation and failure behavior. Three new and revised metrics for energy absorption were proposed to enable more meaningful comparisons and subsequent design selection. Triply Periodic Minimal Surface (TPMS) structures were found to have the most promising overall performance and formed the basis for the numerical investigation of the effect of fields on the energy absorption performance of TPMS structures. A continuum shell-based methodology was developed to analyze the large deformation behavior of field-driven variable thickness TPMS structures and validated against experimental data. A range of analytical and stochastic fields were then evaluated that modified the TPMS structure, some of which were found to be effective in enhancing energy absorption behavior in the structures while retaining the same relative density. Combining findings from studies on the role of cell geometry, composition, relative density, and fields, this thesis concludes with the development of a design framework that can enable the formulation of cellular material energy absorbers with idealized behavior.
ContributorsShinde, Mandar (Author) / Bhate, Dhruv (Thesis advisor) / Peralta, Pedro (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2023