The scope of this project is a combination of material science engineering and<br/>mechanical engineering. Overall, the main goal of this project is to develop a lightweight<br/>concrete that maintains its original strength profile. Initial research has shown that a<br/>plastic-concrete composite could create a more lightweight concrete than that made using the<br/>typical gravel aggregate for concrete, while still maintaining the physical strength that concrete is<br/>known for. This will be accomplished by varying the amount of plastic in the aggregate. If<br/>successful, this project would allow concrete to be used in applications it would typically not be<br/>suitable for.<br/>After testing the strength of the concrete specimens with varying fills of plastic aggregate<br/>it was determined that the control group experienced an average peak stress of 2089 psi, the<br/>16.67% plastic group experienced an average peak stress of 2649 psi, the 33.3% plastic group<br/>experienced an average peak stress of 1852 psi, and the 50% plastic group experienced an<br/>average stress of 924.5 psi. The average time to reach the peak stress was found to be 12 minutes<br/>and 24 seconds in the control group, 15 minutes and 34 seconds in the 16.7% plastic group, 9<br/>minutes and 45 seconds in the 33.3% plastic group, and 10 minutes and 58 seconds in the 50%<br/>plastic group. Taking the average of the normalized weights of the cylindrical samples it was<br/>determined that the control group weighed 14.773 oz/in, the 16.7% plastic group weighed 15<br/>oz/in, the 33.3% plastic group weighed 14.573 oz/in, and the 50% plastic group weighed 12.959<br/>oz/in. Based on these results it can be concluded that a small addition of plastic aggregate can be<br/>beneficial in creating a lighter, stronger concrete. The results show that a 16.7% fill ratio of<br/>plastic to rock aggregate can increase the failure time and the peak strength of a composite<br/>concrete. Overall, the experiment was successful in analyzing the effects of recycled plastic<br/>aggregate in composite concrete.<br/>Some possible future studies related to this subject material are adding aluminum to the<br/>concrete, having better molds, looking for the right consistency in each mixture, mixing for each<br/>mold individually, and performing other tests on the samples.

Polyurea is a highly versatile material used in coatings and armor systems to protect against extreme conditions such as ballistic impact, cavitation erosion, and blast loading. However, the relationships between microstructurally-dependent deformation mechanisms and the mechanical properties of polyurea are not yet fully understood, especially under extreme conditions. In this work, multi-scale coarse-grained models are developed to probe molecular dynamics across the wide range of time and length scales that these fundamental deformation mechanisms operate. In the first of these models, a high-resolution coarse-grained model of polyurea is developed, where similar to united-atom models, hydrogen atoms are modeled implicitly. This model was trained using a modified iterative Boltzmann inversion method that dramatically reduces the number of iterations required. Coarse-grained simulations using this model demonstrate that multiblock systems evolve to form a more interconnected hard phase, compared to the more interrupted hard phase composed of distinct ribbon-shaped domains found in diblock systems. Next, a reactive coarse-grained model is developed to simulate the influence of the difference in time scales for step-growth polymerization and phase segregation in polyurea. Analysis of the simulated cured polyurea systems reveals that more rapid reaction rates produce a smaller diameter ligaments in the gyroidal hard phase as well as increased covalent bonding connecting the hard domain ligaments as evidenced by a larger fraction of bridging segments and larger mean radius of gyration of the copolymer chains. The effect that these processing-induced structural variations have on the mechanical properties of the polymer was tested by simulating uniaxial compression, which revealed that the higher degree of hard domain connectivity leads to a 20% increase in the flow stress. A hierarchical multiresolution framework is proposed to fully link coarse-grained molecular simulations across a broader range of time scales, in which a family of coarse-grained models are developed. The models are connected using an incremental reverse–mapping scheme allowing for long time scale dynamics simulated at a highly coarsened resolution to be passed all the way to an atomistic representation.

Single-layer pentagonal materials have received limited attention compared with their counterparts with hexagonal structures. They are two-dimensional (2D) materials with pentagonal structures, that exhibit novel electronic, optical, or magnetic properties. There are 15 types of pentagonal tessellations which allow plenty of options for constructing 2D pentagonal lattices. Few of them have been explored theoretically or experimentally. Studying this new type of 2D materials with density functional theory (DFT) will inspire the discovery of new 2D materials and open up applications of these materials in electronic and magnetic devices.In this dissertation, DFT is applied to discover novel 2D materials with pentagonal structures. Firstly, I examine the possibility of forming a 2D nanosheet with the vertices of type 15 pentagons occupied by boron, silicon, phosphorous, sulfur, gallium, germanium or tin atoms. I obtain different rearranged structures such as a single-layer gallium sheet with triangular patterns. Then the exploration expands to other 14 types of pentagons, leading to the discoveries of carbon nanosheets with Cairo tessellation (type 2/4 pentagons) and other patterns. The resulting 2D structures exhibit diverse electrical properties. Then I reveal the hidden Cairo tessellations in the pyrite structures and discover a family of planar 2D materials (such as PtP2), with a chemical formula of AB2 and space group pa ̄3. The combination of DFT and geometries opens up a novel route for the discovery of new 2D materials. Following this path, a series of 2D pentagonal materials such as 2D CoS2 are revealed with promising electronic and magnetic applications. Specifically, the DFT calculations show that CoS2 is an antiferromagnetic semiconductor with a band gap of 2.24 eV, and a N ́eel temperature of about 20 K. In order to enhance the superexchange interactions between the ions in this binary compound, I explore the ternary 2D pentagonal material CoAsS, that lacks the inversion symmetry. I find out CoAsS exhibits a higher Curie temperature of 95 K and a sizable piezoelectricity (d11=-3.52 pm/V). In addition to CoAsS, 34 ternary 2D pentagonal materials are discovered, among which I focus on FeAsS, that is a semiconductor showing strong magnetocrystalline anisotropy and sizable Berry curvature. Its magnetocrystalline anisotropy energy is 440 μeV/Fe ion, higher than many other 2D magnets that have been found.
Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices.

The structural and electronic properties of compositionally complex semiconductors have long been of both theoretical interest and engineering importance. As a new class of materials with an intrinsic compositional complexity, medium entropy alloys (MEAs) are immensely studied mainly for their excellent mechanical properties. The electronic properties of MEAs, however, are less well investigated. In this thesis, various properties such as electronic, spin, and thermal properties of two three-dimensional (3D) and two two-dimensional (2D) compositionally complex semiconductors are demonstrated to have promising various applications in photovoltaic, thermoelectric, and spin quantum bits (qubits).3D semiconducting Si-Ge-Sn and C3BN alloys is firstly introduced. Density functional theory (DFT) calculations and Monte Carlo simulations show that the Si1/3Ge1/3Sn1/3 MEA exhibits a large local distortion effect yet no chemical short-range order. Single vacancies in this MEA can be stabilized by bond reformations while the alloy retains semiconducting. DFT and molecular dynamics calculations predict that increasing the compositional disorder in SiyGeySnx MEAs enhances their electrical conductivity while weakens the thermal conductivity at room temperature, making the SiyGeySnx MEAs promising functional materials for thermoelectric devices. Furthermore, the nitrogen-vacancy (NV) center analog in C3BN (NV-C3BN) is studied to explore its applications in quantum computers. This analog possesses similar properties to the NV center in diamond such as a highly localized spin density and strong hyperfine interactions, making C3BN suitable for hosting spin qubits. The analog also displays two zero-phonon-line energies corresponding to wavelengths close to the ideal telecommunication band width, useful for quantum communications.
2D semiconducting transition metal chalcogenides (TMCs) and PtPN are also investigated. The quaternary compositionally complex TMCs show tunable properties such as in-plane lattice constants, band gaps, and band alignment, using a high through-put workflow from DFT calculations in conjunction with the virtual crystal approximation. A novel 2D semiconductor PtPN of direct bandgap is also predicted, based on pentagonal tessellation.
The work in the thesis offers guidance to the experimental realization of these novel semiconductors, which serve as valuable prototypes of other compositionally complex systems from other elements.

Transition metal di- and tri-halides (TMH) have recently gathered research attention owing to their intrinsic magnetism all the way down to their two-dimensional limit. 2D magnets, despite being a crucial component for realizing van der Waals heterostructures and devices with various functionalities, were not experimentally proven until very recently in 2017. The findings opened up enormous possibilities for studying new quantum states of matter that can enable potential to design spintronic, magnetic memory, data storage, sensing, and topological devices. However, practical applications in modern technologies demand materials with various physical and chemical properties such as electronic, optical, structural, catalytic, magnetic etc., which cannot be found within single material systems. Considering that compositional modifications in 2D systems lead to significant changes in properties due to the high anisotropy inherent to their crystallographic structure, this work focuses on alloying of TMH compounds to explore the potentials for tuning their properties. In this thesis, the ternary cation alloys of Co(1-x)Ni(x)Cl(2) and Mo(1-x)Cr(x)Cl(3) were synthesized via chemical vapor transport at a various stoichiometry. Their compositional, structural, and magnetic properties were studied using Energy Dispersive Spectroscopy, Raman Spectroscopy, X-Ray Diffraction, and Vibrating Sample Magnetometry. It was found that completely miscible ternary alloys of Co(1-x)Ni(x)Cl(2) show an increasing Néel temperature with nickel concentration. The Mo(1-x)Cr(x)Cl(3) alloy shows potential magnetic phase changes induced by the incorporation of molybdenum species within the host CrCl3 lattice. Magnetic measurements give insight into potential antiferromagnetic to ferromagnetic transition with molybdenum incorporation, accompanied by a shift in the magnetic easy-axis from parallel to perpendicular. Phase separation was found in the Fe(1-x)Cr(x)Cl(3) ternary alloy indicating that crystallographic structure compatibility plays an essential role in determining the miscibility of two parent compounds. Alloying across two similar (TMH) compounds appears to yield predictable results in properties as in the case of Co(1-x)Ni(x)Cl(2), while more exotic transitions, as in the case of Mo(1-x)Cr(x)Cl(3), can emerge by alloying dissimilar compounds. When dissimilarity reaches a certain limit, as with Fe(1-x)Cr(x)Cl(3), phase separation becomes more favorable. Future studies focusing on magnetic and structural phase transitions will reveal more insight into the effect of alloying in these TMH systems.

Energy return in footwear is associated with the damping behavior of midsole foams, which stems from the combination of cellular structure and polymeric material behavior. Recently, traditional ethyl vinyl acetate (EVA) foams have been replaced by BOOST(TM) foams, thereby reducing the energetic cost of running. These are bead foams made from expanded thermoplastic polyurethane (eTPU), which have a multi-scale structure consisting of fused porous beads, at the meso-scale, and thousands of small closed cells within the beads at the micro-scale. Existing predictive models coarsely describe the macroscopic behavior but do not take into account strain localizations and microstructural heterogeneities. Thus, enhancement in material performance and optimization requires a comprehensive understanding of the foam’s cellular structure at all length scales and its influence on mechanical response.

This dissertation focused on characterization and deformation behavior of eTPU bead foams with a unique graded cell structure at the micro and meso-scale. The evolution of the foam structure during compression was studied using a combination of in situ lab scale and synchrotron x-ray tomography using a four-dimensional (4D, deformation + time) approach. A digital volume correlation (DVC) method was developed to elucidate the role of cell structure on local deformation mechanisms. The overall mechanical response was also studied ex situ to probe the effect of cell size distribution on the force-deflection behavior. The radial variation in porosity and ligament thickness profoundly influenced the global mechanical behavior. The correlation of changes in void size and shape helped in identifying potentially weak regions in the microstructure. Strain maps showed the initiation of failure in cell structure and it was found to be influenced by the heterogeneities around the immediate neighbors in a cluster of voids. Poisson’s ratio evaluated from DVC was related to the microstructure of the bead foams. The 4D approach taken here provided an in depth and mechanistic understanding of the material behavior, both at the bead and plate levels, that will be invaluable in designing the next generation of high-performance footwear.

Additive manufacturing (AM) has been extensively investigated in recent years to explore its application in a wide range of engineering functionalities, such as mechanical, acoustic, thermal, and electrical properties. The proposed study focuses on the data-driven approach to predict the mechanical properties of additively manufactured metals, specifically Ti-6Al-4V. Extensive data for Ti-6Al-4V using three different Powder Bed Fusion (PBF) additive manufacturing processes: Selective Laser Melting (SLM), Electron Beam Melting (EBM), and Direct Metal Laser Sintering (DMLS) are collected from the open literature. The data is used to develop models to estimate the mechanical properties of Ti-6Al-4V. For this purpose, two models are developed which relate the fabrication process parameters to the static and fatigue properties of the AM Ti-6Al-4V. To identify the behavior of the relationship between the input and output parameters, each of the models is developed on both linear multi-regression analysis and non-linear Artificial Neural Network (ANN) based on Bayesian regularization. Uncertainties associated with the performance prediction and sensitivity with respect to processing parameters are investigated. Extensive sensitivity studies are performed to identify the important factors for future optimal design. Some conclusions and future work are drawn based on the proposed study with investigated material.

Granular material can be found in many industries and undergo process steps like drying, transportation, coating, chemical, and physical conversions. Understanding and optimizing such processes can save energy as well as material costs, leading to improved products. Silica beads are one such granular material encountered in many industries as a catalyst support material. The present research aims to obtain a fundamental understanding of the hydrodynamics and heat transfer mechanisms in silica beads. Studies are carried out using a hopper discharge bin and a rotary drum, which are some of the most common process equipment found in various industries. Two types of micro-glass beads with distinct size distributions are used to fill the hopper in two possible packing arrangements with varying mass ratios. For the well-mixed configuration, the fine particles clustered at the hopper bottom towards the end of the discharge. For the layered configuration, the coarse particles packed at the hopper bottom discharge first, opening a channel for the fine particles on the top. Also, parameters such as wall roughness (WR) and particle roughness (PR) are studied by etching the particles. The discharge rate is found to increase with WR, and found to be proportional to (Root mean square of PR)^(-0.58). Furthermore, the drum is used to study the conduction and convection heat transfer behavior of the particle bed with varying process conditions. A new non-invasive temperature measurement technique is developed using infrared thermography, which replaced the traditional thermocouples, to record the temperatures of the particles and the drum wall. This setup is used to understand the flow regimes of the particle bed inside the drum and the heat transfer mechanisms with varying process conditions. The conduction heat transfer rate is found to increase with decreasing particle size, decreasing fill level, and increasing rotation speed. The convection heat transfer rate increased with increasing fill level and decreasing particle size, and rotation speed had no significant effect. Due to the complexities in these systems, it is not always possible to conduct experiments, therefore, heat transfer models in Discrete Element Method codes (MFIX-DEM: open-source code, and EDEM: commercial code) are adopted, validated, and the effects of model parameters are studied using these codes.

Single drop impact of liquid on a static powder bed was studied to investigate the granule formation mechanism, droplet penetration time, the characterization of granules (morphology, surface structure and internal structure), as well as the formation regime map. Water was used as the liquid and two pharmaceutical powders, microcrystalline cellulose (MCC) and acetaminophen (APAP), were mixed to make heterogeneous powder beds. The complete drop impact and penetration was recorded by a high-speed camera. Two granule formation mechanisms identified previously occurred: Spreading and Tunneling. Spreading occurred for mixtures of large particle sizes, while Tunneling started to occur when the particle sizes of the mixtures decreased. With an increase of APAP concentration, the overall drop penetration time increased, which was in good agreement with previous literature. The granule morphology, surface structure, and internal structure were characterized by a prism method with image analysis, scanning electron microscope, and X-ray microtomography, respectively. The Spreading mechanism produced flat disks with porous internal structures, while the Tunneling mechanism produced round granules with dense internal structures. Granules that were formed via a hybrid of the mechanisms, Spreading/Tunneling, were hybrid granules, with some dense areas and some porous areas. The results of the granule content uniformity from UV-vis spectrometry revealed that with the increase of APAP proportion, the overall uniformity was compromised for mixtures with fine ingredients, while the content was much more uniform for coarse mixtures. It is believed that the mean particle size of the powder bed is the predominant factor in influencing the formation mechanism, drop penetration time, and granule properties, while the content uniformity is affected by both the particle sizes and the mixture hydrophobicity.

Precursors of carbon fibers include rayon, pitch, and polyacrylonitrile fibers that can be heat-treated for high-strength or high-modulus carbon fibers. Among them, polyacrylonitrile has been used most frequently due to its low viscosity for easy processing and excellent performance for high-end applications. To further explore polyacrylonitrile-based fibers for better precursors, in this study, carbon nanofillers were introduced in the polymer matrix to examine their reinforcement effects and influences on carbon fiber performance. Two-dimensional graphene nanoplatelets were mainly used for the polymer reinforcement and one-dimensional carbon nanotubes were also incorporated in polyacrylonitrile as a comparison. Dry-jet wet spinning was used to fabricate the composite fibers. Hot-stage drawing and heat-treatment were used to evolve the physical microstructures and molecular morphologies of precursor and carbon fibers. As compared to traditionally used random dispersions, selective placement of nanofillers was effective in improving composite fiber properties and enhancing mechanical and functional behaviors of carbon fibers. The particular position of reinforcement fillers with polymer layers was enabled by the in-house developed spinneret used for fiber spinning. The preferential alignment of graphitic planes contributed to the enhanced mechanical and functional behaviors than those of dispersed nanoparticles in polyacrylonitrile composites. The high in-plane modulus of graphene and the induction to polyacrylonitrile molecular carbonization/graphitization were the motivation for selectively placing graphene nanoplatelets between polyacrylonitrile layers. Mechanical tests, scanning electron microscopy, thermal, and electrical properties were characterized. Applications such as volatile organic compound sensing and pressure sensing were demonstrated.