Advanced mechanics of materials with microstructure

The study of advanced materials aimed at improving human life has been performed since time immemorial. Such studies have created everlasting and greatly revered monuments and have helped revolutionize transportation by ushering the age of lighter–than–air flying machines. Hence a study of the mechanical behavior of advanced materials can pave way for their use for mankind’s benefit. In this school of thought, the aim of this dissertation is to broadly perform two investigations. First, an efficient modeling approach is established to predict the elastic response of cellular materials with distributions of cell geometries. Cellular materials find important applications in structural engineering. The approach does not require complex and time-consuming computational techniques usually associated with modeling such materials. Unlike most current analytical techniques, the modeling approach directly accounts for the cellular material microstructure. The approach combines micropolar elasticity theory and elastic mixture theory to predict the elastic response of cellular materials. The modeling approach is applied to the two dimensional balsa wood material. Predicted properties are in good agreement with experimentally determined properties, which emphasizes the model’s potential to predict the elastic response of other cellular solids, such as open cell and closed cell foams. The second topic concerns intraneural ganglion cysts which are a set of medical conditions that result in denervation of the muscles innervated by the cystic nerve leading to pain and loss of function. Current treatment approaches only temporarily alleviate pain and denervation which, however, does not prevent cyst recurrence. Hence, a mechanistic understanding of the pathogenesis of intraneural ganglion cysts can help clinicians understand them better and therefore devise more effective treatment options. In this study, an analysis methodology using finite element analysis is established to investigate the pathogenesis of intraneural ganglion cysts. Using this methodology, the propagation of these cysts is analyzed in their most common site of occurrence in the human body i.e. the common peroneal nerve. Results obtained using finite element analysis show good correlation with clinical imaging patterns thereby validating the promise of the method to study cyst pathogenesis.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

Effect of microstructure and alloying elements on the resistance of fastener grade steels to hydrogen assisted cracking

Fastener grade steels with varying alloy contents and heat treatments were employed to measure changes in resistance to hydrogen assisted cracking. The testing procedure compared notched tension specimens fractured in air to threshold stress values obtained during hydrogen charging, utilizing a rising step load procedure. Bainitic structures improved resistance by 10-20% compared to tempered martensite structures. Dual phase steels with a tempered martensite matrix and 20% ferrite were more susceptible and notch sensitive. High strength, fully pearlitic structures showed an improvement in resistance. Carbon content, per se, had no effect on the resistance of steel to hydrogen assisted cracking. Chromium caused a deleterious effect but all other alloying elements studied did not cause much change in hydrogen assisted cracking susceptibility.

Experimental and theoretical study of microstructure effect on piezoelectric property of one dimensional ZnO nanostructures

Emerging nanogenerators have attracted the attention of the research community, focusing on energy generation using piezoelectric nanomaterials. Nanogenerators can be utilized for powering NEMS/MEMS devices. Understanding the piezoelectric properties of ZnO one-dimensional materials such as ZnO nanobelts (NBs) and Nanowires (NWs) can have a significant impact on the design of new devices. The goal of this dissertation is to study the piezoelectric properties of one-dimensional ZnO nanostructures both experimentally and theoretically. First, the experimental procedure for producing the ZnO nanostructures is discussed. The produced ZnO nanostructures were characterized using an in-situ atomic force microscope and a piezoelectric force microscope. It is shown that the electrical conductivity of ZnO NBs is a function of applied mechanical force and its crystalline structure. This phenomenon was described in the context of formation of an electric field due to the piezoelectric property of ZnO NBs. In the PFM studies, it was shown that the piezoelectric response of the ZnO NBs depends on their production method and presence of defects in the NB. Second, a model was proposed for making nanocomposite electrical generators based on ZnO nanowires. The proposed model has advantages over the original configuration of nanogenerators which uses an AFM tip for bending the ZnO NWs. Higher stability of the electric source, capability for producing larger electric fields, and lower production costs are advantages of this configuration. Finally, piezoelectric properties of ZnO NBs were simulated using the molecular dynamics (MD) technique. The size-scale effect on piezoelectric properties of ZnO NBs was captured, and it is shown that the piezoelectric coefficient of ZnO NBs decreases by increasing their lateral dimensions. This phenomenon is attributed to the surface charge redistribution and compression of unit cells that are placed on the outer shell of ZnO NBs.

COMPUTATIONAL STUDY OF MICROSTRUCTURE-PROPERTYMECHANISM RELATIONS IN FERROIC COMPOSITES

Ferroic materials, as notable members of smart materials, have been widely used in applications that perform sensing, actuation and control. The macroscopic property change of ferroic materials may become remarkably large during ferroic phase transition, leading to the fact that the macroscopic properties can be tuned by carefully applying a suitable external field (electric, magnetic, stress). To obtain an enhancement in physical and/or mechanical properties, different kinds of ferroic composites have been fabricated. The properties of a ferroic composite are determined not only by the properties and relative amounts of the constituent phases, but also by the microstructure of individual phase such as the phase connectivity, phase size, shape and spatial arrangement. This dissertation mainly focuses on the computational study of microstructure – property – mechanism relations in two representative ferroic composites, i.e., two-phase particulate magnetoelectric (ME) composite and polymer matrix ferroelectric composite. The former is a great example of ferroic composite exhibiting a new property and functionality that neither of the constituent phases possesses individually. The latter well represents the kind of ferroic composites having property combinations that are better than the existing materials. Phase field modeling was employed as the computing tool, and the required models for ferroic composites were developed based on existing models for monolithic materials. Extensive computational simulations were performed to investigate the microstructure-property relations and the underlying mechanism in ferroic composites. In particulate, it is found that for ME composite 0-3 connectivity (isolated magnetostrictive phase) is necessary to exhibit ME effect, and small but finite electrical conductivity of isolated magnetic phase can beneficially enhance ME effect. It is revealed that longitudinal and transverse ME coefficients of isotropic 0-3 particulate composites can be effectively tailored by controlling magnetic domain structures without resort to anisotropic two-phase microstructures. Simulations also show that the macroscopic properties of the ferroelectricpolymer composites critically depend on the ferroelectric phase connectivity while are not sensitive to the sizes and internal grain structures of the ceramic particles. Texturing is found critical to exploit the paraelectric«ferroelectric phase transition and nonlinear polarization behavior in paraelectric polycrystal and its polymer matrix composite. Additionally, a Diffuse Interface Field model was developed to simulate packing and motion in liquid phase which is promising for studying the fabrication of particulatepolymer composites.

THE POTENTIAL OF INDUSTRIAL WASTE AND AGRICULTURAL FEEDSTOCK TOWARDS SUSTAINABLE BIOFUELS PRODUCTION: TECHNO-ECONOMIC AND ENVIRONMENTAL IMPACT PERSPECTIVES

This Ph.D. research is comprised of three major components; (i) Characterization study to analyze the composition of defatted corn syrup (DCS) from a dry corn mill facility (ii) Hydrolysis experiments to optimize the production of fermentable sugars and amino acid platform using DCS and (iii) Sustainability analyses. Analyses of DCS included total solids, ash content, total protein, amino acids, inorganic elements, starch, total carbohydrates, lignin, organic acids, glycerol, and presence of functional groups. Total solids content was 37.4% (± 0.4%) by weight, and the mass balance closure was 101%. Total carbohydrates [27% (± 5%) wt.] comprised of starch (5.6%), soluble monomer carbohydrates (12%) and non-starch carbohydrates (10%). Hemicellulose components (structural and non-structural) were; xylan (6%), xylose (1%), mannan (1%), mannose (0.4%), arabinan (1%), arabinose (0.4%), galatactan (3%) and galactose (0.4%). Based on the measured physical and chemical components, bio-chemical conversion route and subsequent fermentation to value added products was identified as promising. DCS has potential to serve as an important fermentation feedstock for bio-based chemicals production. In the sugar hydrolysis experiments, reaction parameters such as acid concentration and retention time were analyzed to determine the optimal conditions to maximize monomer sugar yields while keeping the inhibitors at minimum. Total fermentable sugars produced can reach approximately 86% of theoretical yield when subjected to dilute acid pretreatment (DAP). DAP followed by subsequent enzymatic hydrolysis was most effective for 0 wt% acid hydrolysate samples and least efficient towards 1 and 2 wt% acid hydrolysate samples. The best hydrolysis scheme DCS from an industry's point of view is standalone 60 minutes dilute acid hydrolysis at 2 wt% acid concentration. The combined effect of hydrolysis reaction time, temperature and ratio of enzyme to substrate ratio to develop hydrolysis process that optimizes the production of amino acids in DCS were studied. Four key hydrolysis pathways were investigated for the production of amino acids using DCS. The first hydrolysis pathway is the amino acid analysis using DAP. The second pathway is DAP of DCS followed by protein hydrolysis using proteases [Trypsin, Pronase E (Streptomyces griseus) and Protex 6L]. The third hydrolysis pathway investigated a standalone experiment using proteases (Trypsin, Pronase E, Protex 6L, and Alcalase) on the DCS without any pretreatment. The final pathway investigated the use of Accellerase 1500® and Protex 6L to simultaneously produce fermentable sugars and amino acids over a 24 hour hydrolysis reaction time. The 3 key objectives of the techno-economic analysis component of this PhD research included; (i) Development of a process design for the production of both the sugar and amino acid platforms with DAP using DCS (ii) A preliminary cost analysis to estimate the initial capital cost and operating cost of this facility (iii) A greenhouse gas analysis to understand the environmental impact of this facility. Using Aspen Plus®, a conceptual process design has been constructed. Finally, both Aspen Plus Economic Analyzer® and Simapro® sofware were employed to conduct the cost analysis as well as the carbon footprint emissions of this process facility respectively. Another section of my PhD research work focused on the life cycle assessment (LCA) of commonly used dairy feeds in the U.S. Greenhouse gas (GHG) emissions analysis was conducted for cultivation, harvesting, and production of common dairy feeds used for the production of dairy milk in the U.S. The goal was to determine the carbon footprint [grams CO2 equivalents (gCO2e)/kg of dry feed] in the U.S. on a regional basis, identify key inputs, and make recommendations for emissions reduction. The final section of my Ph.D. research work was an LCA of a single dairy feed mill located in Michigan, USA. The primary goal was to conduct a preliminary assessment of dairy feed mill operations and ultimately determine the GHG emissions for 1 kilogram of milled dairy feed.