The mass of carbon trapped in methane hydrates exceeds that in conventional fossil fuel reservoirs. While methane in coarse-grained hydrate-bearing sediments is technically recoverable, most methane hydrates are found in fine-grained marine sediments where gas recovery is inherently impeded by very low gas permeability. Using experimental methods and analyses, this thesis advances the understanding of fine-grained sediments in view of gas production from methane hydrates. The research scope includes: a new approach for the classification of fines in terms of electrical sensitivity, the estimation of the sediment volume contraction during hydrate dissociation, a pore-scale study of gas migration in sediments and the self-regulation effect of surfactants, the formation of preferential gas migration pathways at interfaces during gas production, pressure core technology for the characterization of hydrate bearing sediments without causing hydrate dissociation, and the deployment of a bio-sub-sampling chamber in Japan.

The purpose of this thesis was to characterize cancer metabolism in vitro using epithelial ovarian cancer as a model on an untargeted, systems-level, basis with particular attention paid to the difference between cancer stem cell metabolism and cancer cell metabolism. Two-dimensional gas chromatography coupled to mass spectrometry was used to measure the metabolite profiles of the ovarian cancer and cancer stem cell lines under normal baseline conditions and also under chemotherapeutic and environmental perturbations. These two cell lines exhibited significant metabolic differences under normal baseline conditions and results demonstrated that metabolism in the ovarian cancer stem cell line was distinct from that of more differentiated isogenic cancer cells, showing similarities to stem cell metabolism that suggest the potential importance of metabolism for the cancer stem cell phenotype. Glucose deprivation, hypoxia, and ischemia all perturbed ovarian cancer and cancer stem cell metabolism, but not in the same ways between the cell types. Chemotherapeutic treatment with docetaxel caused metabolic changes mostly in amino acid and carbohydrate metabolism in ovarian cancer cells, while ovarian cancer stem cell metabolism was not affected by docetaxel. Overall, these metabolic differences between the two cell types will deepen our understanding of the metabolic changes occurring within the in vivo tumor and will help drive development of cancer stem cell targeted therapeutics.

This research investigates the environment and development issues of three stakeholders at multiple scales—global, national, regional, and local. Through the analysis of financial, social, and environmental metrics, the potential benefits and risks of each case study are estimated, and their implications are considered. In the first case study, the relationship of manufacturing and environmental performance is investigated. Over 700 facilities of a global manufacturer that produce 11 products on six continents were investigated to understand global variations and determinants of environmental performance. Water, energy, carbon dioxide emissions, and production data from these facilities were analyzed to assess environmental performance; the relationship of production composition at the individual firm and environmental performance were investigated. Location-independent environmental performance metrics were combined to provide both global and local measures of environmental performance. These models were extended to estimate future water use, energy use, and greenhouse gas emissions considering potential demand shifts. Natural resource depletion risks were investigated, and mitigation strategies related to vulnerabilities and exposure were discussed. The case study demonstrated how data from multiple facilities can be used to characterize the variability amongst facilities and to preview how changes in production may affect overall corporate environmental metrics. The developed framework adds a new approach to account for environmental performance and degradation as well as assess potential risk in locations where climate change may affect the availability of production resources (i.e., water and energy) and thus, is a tool for understanding risk and maintaining competitive advantage. The second case study was designed to address the issue of delivering affordable and sustainable energy. Energy pricing was evaluated by modeling individual energy consumption behaviors. This analysis simulated a heterogeneous set of residential households in both the urban and rural environments in order to understand demand shifts in the residential energy end-use sector due to the effects of electricity pricing. An agent-based model (ABM) was created to investigate the interactions of energy policy and individual household behaviors; the model incorporated empirical data on beliefs and perceptions of energy. The environmental beliefs, energy pricing grievances, and social networking dynamics were integrated into the ABM model structure. This model projected the aggregate residential sector electricity demand throughout the 30-year time period as well as distinguished the respective number of households who only use electricity, that use solely rely on indigenous fuels, and that incorporate both indigenous fuels and electricity. The model is one of the first characterizations of household electricity demand response and fuel transitions related to energy pricing at the individual household level, and is one of the first approaches to evaluating consumer grievance and rioting response to energy service delivery. The model framework is suggested as an innovative tool for energy policy analysis and can easily be revised to assist policy makers in other developing countries. In the final case study, a framework was developed for a broad cost-benefit and greenhouse gas evaluation of transit systems and their associated developments. A case study was developed of the Atlanta BeltLine. The net greenhouse gas emissions from the BeltLine light rail system will depend on the energy efficiency of the streetcars themselves, the greenhouse gas emissions from the electricity used to power the streetcars, the extent to which people use the BeltLine instead of driving personal vehicles, and the efficiency of their vehicles. The effects of ridership, residential densities, and housing mix on environmental performance were investigated and were used to estimate the overall system efficacy. The range of the net present value of this system was estimated considering health, congestion, per capita greenhouse gas emissions, and societal costs and benefits on a time-varying scale as well as considering the construction and operational costs. The 95% confidence interval was found with a range bounded by a potential loss of $860 million and a benefit of $2.3 billion; the mean net present value was $610 million. It is estimated that the system will generate a savings of $220 per ton of emitted CO2 with a 95% confidence interval bounded by a potential social cost of $86 cost per ton CO2 and a savings of $595 per ton CO2.

Recent years have seen increasing research interest in structural health monitoring (SHM). Among the many advances in SHM research, “smart” wireless sensors capable of embedded computing and wireless communication have been highly attractive. Wireless communication in SHM systems was originally proposed to significantly reduce the monetary and time cost for installing lengthy cables in an SHM system. Besides wireless sensing, the next revolution in sensor networks has been predicted to be mobile sensor networks that implant mobility into traditional wireless sensor networks. This research explores decentralized structural model updating and damage detection using mobile and wireless sensors. In the first stage of this research, mobile sensing nodes (MSNs) are developed for SHM purposes. The MSNs can maneuver upon structures built with ferromagnetic/steel materials, conduct measurement, and communicate with pears or remote servers wirelessly. The performance of the MSNs is validated through laboratory and field experiments. To further investigate the mobile sensing strategy, a decentralized structural damage detection procedure is proposed herein for the MSNs using transmissibility functions. Laboratory experiments are conducted on a steel portal frame where various structure damage scenarios are emulated. Besides experiments with MSNs, this study also investigates the nature of transmissibility functions for damage detection in an analytical manner based on a general multi-DOF spring-mass-damper system. Finally, this research also explores substructure model updating through minimization of modal dynamic residuals, which can best benefit from dense mobile or wireless sensor data concentrated in one area. Craig-Bampton transform is adopted to condense the structural model, and minimization of the modal dynamic residuals is determined as the optimization objective. An iterative linearization procedure is adopted for efficiently solving the optimization problem. The presented substructure updating method is validated through a few numerical examples. For comparison, a conventional approach minimizing modal property differences is also applied, and shows worse updating accuracy than the proposed approach. The performance of the proposed substructure model updating approach is further investigated on the effects of substructure location and size.

The two main requirements for ceria-zirconia hydrodeoxygenation (HDO) catalysts are the presence of defect sites to bind oxygenates and the ability to adsorb and dissociate hydrogen. Two types of sites were identified for exchange of hydrogen and deuterium. The activation energy for one type of site was associated with H2-D2 exchange through oxygen defect sites. The activation energy for the second type of site was associated with H2-D2 exchange through hydroxyl groups and correlated with crystallite size. Ceria-zirconia can convert guaiacol, a model pyrolysis oil compound, with a high selectivity to phenol, an HDO product. Ceria-zirconia catalysts had a higher conversion of guaiacol to deoxygenated products as well as a higher selectivity towards phenol than pure ceria. They did not deactivate over the course of 72 hours on stream, whereas coking or the presence of water in the feed can cause serious decay of common HDO catalysts HDO. Therefore, ceria-zirconia catalysts are promising HDO catalysts for the first step of deoxygenation. The stability of supported Ru on ZrO2 in acidic or basic environments at reaction temperature is examined. In this study, the ruthenium dispersion is greatly increased by hydrothermal treatment in acidic and basic pH without alterations to the surface area, pore volume, pore size or crystal structure. An increase in Ru dispersion showed an increase in the selectivity to propylene glycol relative to ethylene glycol. A decrease in total Lewis acid site concentration was correlated with a decrease in the ethylene glycol yield. The conclusions of this study indicate that stability of catalysts in realistic industrial environments is crucial to the design of catalysts for a reaction.

This study focuses on the design, fabrication, and characterization of deterministically engineered, three-dimensional architectures to be used as high-performance electrodes in energy storage applications. These high-surface-area architectures are created by the robotically-assisted sequential electrodeposition of structural and sacrificial layers in an alternating fashion, followed by the removal of the sacrificial layers. The primary goal of this study is the incorporation of these highly laminated architectures into the battery electrodes to improve their power density without compromising their energy density. MEMS technologies, as well as electrochemical techniques, are utilized for the realization of these high-power electrodes with precisely controlled characteristic dimensions. Diffusion-limited models are adopted for the determination of the optimum characteristic dimensions of the electrodes, including the surface area, the thickness of the active material film, and the distance between the adjacent layers of the multilayer structure. The contribution of the resultant structures to the power performance is first demonstrated by a proof-of-concept Zn-air microbattery which is based on a multilayer Ni backbone coated with a conformal Zn film serving as the anode. This primary battery system demonstrates superior performance to its thin-film counterpart in terms of the energy density at high discharge rates. Another demonstration involves secondary battery chemistries, including Ni(OH)2 and Li-ion systems, both of which exhibit significant cycling stability and remarkable power capability by delivering more than 50% of their capacities after ultra-fast charge rates of 60 C. Areal capacities as high as 5.1 mAh cm-2 are reported. This multilayer fabrication approach is also proven successful for realizing high-performance electrochemical capacitors. Ni(OH)2-based electrochemical capacitors feature a relatively high areal capacitance of 1319 mF cm-2 and an outstanding cycling stability with a 94% capacity retention after more than 1000 cycles. The improved power performance of the electrodes is realized by the simultaneous minimization of the internal resistances encountered during the transport of the ionic and electronic species at high charge and discharge rates. The high surface area provided by the highly laminated backbone structures enables an increased number of active sites for the redox reactions. The formation of a thin and conformal active material film on this high surface area structure renders a reduced ionic diffusion and electronic conduction path length, mitigating the power-limiting effect of the active materials with low conductivities. Also, the highly conductive backbone serving as a mechanically stable and electrochemically inert current collector features minimized transport resistance for the electrons. Finally, the highly scalable nature of the multilayer structures enables the realization of high-performance electrodes for a wide range of applications from autonomous microsystems to macroscale portable electronic devices.

Subsurface volume loss takes place in many geotechnical situations, and it is inherently accompanied by complex stress and displacement fields that may influence the performance of engineered geosystems. This research is a deformation-centered analysis, it depends on soil compressibility and it is implemented using finite elements. Soil stiffness plays a central role in predicting ground deformation. First, an enhanced Terzaghi’s soil compressibility model is proposed to satisfy asymptotic conditions at low and high stress levels with a small number of physically meaningful parameters. Then, the difference between small and large strain stiffness is explored using published small and large-strain stress-strain data. Typically, emphasis is placed on the laboratory-measured stiffness or compressibility; however, there are pronounced differences between laboratory measurements and field values, in part due to seating effects that prevail in small-thickness oedometer specimens. Many geosystems are subjected to repetitive loads; volumetric strains induced by drained repetitive ko-loads are experimentally investigated to identify shakedown and associated terminal density. The finite element numerical simulation environment is used to explore the effect of localized subsurface mass loss on free-surface deformation and shallow foundations settlement and bearing capacity. A stress relaxation module is developed to reproduce the change in stress associated to dissolution features and soft zone formation. The comprehensive parametric study is summarized in terms of dimensionless ratios that can be readily used for engineering applications. Field settlement data gathered at the Savannah River Site SRS are back-analyzed to compare measured values with predictions based on in situ shear wave velocity and strain-dependent stiffness reduction. The calibrated model is used to estimate additional settlements due to the pre-existing cavities, new cavities, and potential seismic events during the design life of the facility.

Thiopeptides are posttranslationally-processed macrocyclic peptide metabolites, characterized by extensive backbone and side chain modifications that include a six-membered nitrogenous ring, thioazol(in)e/oxazol(in)e rings, and dehydrated amino acid residues. Thiostrepton A, produced by Streptomyces laurentii ATCC 31255, is one of the more structurally complex thiopeptides, containing a second macrocycle bearing a quinaldic acid. Thiostrepton A and other thiopeptides are of great interest due to their potent activities against emerging antibiotic-resistant Gram-positive pathogens, in addition to their antimalarial and anticancer properties. The ribosomal origins for thiopeptides have been established, however, few details are known concerning the posttranslational modification steps. Alteration to the primary amino acid sequence of the precursor peptide provides an avenue to probe the substrate specificity of the thiostrepton A posttranslational machinery. The information gathered from current studies can also be used to refine thiostrepton’s structure-activity relationship, providing insight into the key features of its scaffold that impart specificity toward each biological target. A fosmid-dependent biosynthetic engineering platform for thiostrepton A was developed and a series of thiostrepton analogs were successfully produced adapting this method. The seventh residue of thiostrepton A is predicted to be critical for the metabolite’s antibacterial activity. Our results were consistent this hypothesis and demonstrated that substitution of Thr7 in the thiostrepton A precursor peptide disrupts both biological activity and successful biosynthesis of the analogs. The thiostrepton biosynthetic machinery’s tolerances toward structural variation at the second and fourth positions of the TsrA core peptide were probed by the saturation mutagenesis of Ala2 and Ala4, respectively. Eight thiostrepton Ala2 variants were isolated with two analogs truncated at the N-terminus by one amino acid, bearing a shortened quinaldic acid-containing macrocycle. Our results suggested that the identity of the core peptide second residue influences the biosynthesis of a thiostrepton analog, however, not essential for the antibacterial and proteasome inhibitory activities of the full-length variants. Additionally, the quinaldic acid loop size affects thiostrepton’s antibacterial potency, but is not critical for the proteasome inhibitory activity. Sixteen thiostrepton analogs were isolated from Ala4 mutagenesis studies. We demonstrated that the identity of the amino acid residue at the fourth position in the thiostrepton scaffold is not critical to inhibit either the ribosome or the proteasome in vitro.

The localization and translation of messenger ribonucleic acids (mRNAs) play crucial roles in cellular function and diseases, and are regulated by numerous RNA-binding proteins (RBPs) and small non-coding RNAs, called trans-acting factors. Biochemical and imaging methods used to study RNA interactions with these trans-acting elements have made important discoveries in characterizing how these factors regulate gene expression and determining the RNA sequence to which they bind. However, the spatiotemporal information regarding these interactions in subcellular compartments have been difficult to determine or to quantify accurately. To image and quantify native RNA and RNA–protein interactions simultaneously in situ, we developed a proximity ligation assay that combines peptide-modified RNA imaging probes. It can detect the RNAs in live cells and the interactions at a single-interaction level. Lastly, it can produce results that are easily quantifiable. We tested the specificity and sensitivity of this technique using two models: interactions between the genomic RNA and the N protein of human respiratory syncytial virus as well as those between exogenous transcripts with or without the Human antigen R (HuR) binding site and HuR. To validate this method, its accuracy and utility have been demonstrated in three models: poly(A)+ or β-actin mRNAs binding to different cytoskeleton for localization, poly(A)+ or β-actin mRNAs interacting with HuR for stabilization, and programmed cell death 4 (PDCD4) mRNA binding to HuR or T-cell intracellular antigen (TIA1) for translational regulation.

Conjugated polymers have attracted much interest as promising alternatives to inorganic semiconductors, due to their low-temperature, solution-based processability, which may provide for low-cost, large-area electronic device fabrication. However, commercialization of polymer-based electronic devices has been restricted owing to low device performance of solidified thin-films. In order to enhance charge transport of polymer semiconductor thin-films, the self-organization of organic polymer semiconductors into ordered supramolecular assemblies has been achieved by tuning a range of process parameters including film deposition method (spin vs. drop cast), solvent boiling point (low vs. high boiling point), polymer-dielectric interface treatment, and post-deposition processing (solvent vapor or thermal annealing). However, these strategies give rise to limitations for large-scale high-throughput processing due to associated pre- and/or post semiconductor deposition steps. Therefore, in this thesis, we identify alternative processing parameters (i.e., hydrogen bonds between good and poor solvents, UV irradiation to polymer precursor solutions, and combination of sonication and subsequent UV irradiation to polymer precursor solutions) which can contribute to enhancement in charge transport of a model polymer semiconductor, poly(3-hexylthiophene) (P3HT), eliminating the additional pre- and/or post-steps mentioned above. Further, we understand of how the processing parameters effect intra- and intermolecular interactions of the polymer chains, micro- through macroscopic morphologies, and charge transport characteristics of the resultant films.