Expansion microscopy (ExM) assumes biological specimens and the hydrogel expand isotropically, but distortions are often observed and are typically corrected in two dimensions, without addressing their three-dimensional structure or physical origin. Here, I treat the hydrogel as an independent material system and develop a quantitative framework to model its intrinsic deformation during expansion in 3D. Photoactivatable fluorescent fiducial beads were embedded throughout polyacrylamide gels and imaged pre- and post-expansion. I built a 3D registration pipeline based on polyharmonic spline modeling to reconstruct the full volumetric deformation field. Unlike existing slice-by-slice 2D correction methods, this framework captures out-of-plane distortions invisible to planar analysis and yields a continuous mathematical description of the deformation field. The results show that non-uniform expansion arises from intrinsic hydrogel properties rather than biological sample effects, allowing material-driven distortion to be quantitatively separated from specimen-specific contributions. Quantifying this baseline behavior enables separation of material-driven distortion from specimen-specific contributions and provides a framework for engineering ExM protocols with uniform expansion.

In humans, the composition and abundance of microbial species that reside inside the intestinal tract– termed the gut microbiome– plays an integral role in health. These microbes produce essential nutrients, modulate metabolic pathways, and promote immune system function [1, 2]. As such, gut microbiome dysbiosis– a disturbance from the homeostatic microbiome– is associated with various health complications, such as Irritable Bowel Syndrome, obesity, and Type-II Diabetes [3]. Beyond modulating physical health, the features of the gut microbiome also impact neurological activity and cognitive function via a bi-directional signaling pathway known as the gut-brain axis. Over the past decade, studies of this axis have revealed correlations between microbiome composition and the progression of neurodegenerative diseases such as Alzheimer’s and Parkinson’s, as well as mental illnesses such as anxiety and depression [4]. Here, we use the common fruit fly, Drosophila melanogaster, as a model organism for studying the gut-brain axis. With the aim of not only assessing the impact of the gut microbiome on stereotyped fly behaviors, but also exploring its effect on Drosophila circadian rhythms, we collect and analyze data over a 24-hour imaging window. We utilize high-resolution pose tracking and subsequent behavioral mapping to extract information regarding six stereotyped behaviors: locomotion, fore grooming, hind grooming, wing grooming, proboscis extension, and idle. From this data, we find that the daytime activity level and overall behavioral state of non-virgin female D. melanogaster is less sensitive to microbiome perturbations than that of non-virgin male Drosophila. Among male populations, we observe increased daytime activity levels following antibiotic treatment, which are rescued via monocolonization with Lactobacillus brevis and Lactobacillus plantarum. We also find that the circadian rhythms of female D. melanogaster are stabilized by the presence of a gut microbiome, as, upon microbiome removal, their night-day behavioral difference becomes more defined. This trend is not observed in male populations. Broadly, this project motivates the development and implementation of novel treatment methods for neurological disorders through high-resolution behavioral analysis of the Drosophila melanogaster gut-brain axis.

The chemical termination of the diamond (100) surface plays a critical role in determining the performance of near-surface nitrogen-vacancy (NV) centers, which are promising platforms for emerging quantum sensing and computing technology. Oxygen-termination of the diamond (100) surface produces favorable conditions for NV center applications. On this surface, carbonyl (C=O) and (C–O–C) terminations coexist. The carbonyl termination likely introduces magnetic noise and is an undesirable termination. These two states’ relative stability at finite temperatures and near defects remains unclear. In this work, molecular dynamics (MD) simulations with enhanced sampling techniques, including on-the-fly probability enhanced sampling (OPES), are used to construct free-energy surfaces for monolayer coverage of oxygen on diamond (100). For ideal surfaces, ether is favored at low temperatures, with carbonyl becoming increasingly stable as temperature rises. Free-energy differences between states predict approximately 90% ether coverage at 300 K, consistent with prior studies. In contrast, substitution defects locally favor carbonyl at 600 K and perturb oxygen bonding environments over distances exceeding 12 ˚A.

This study evaluates how the representation of thermal generator start-up and shutdown behavior in capacity expansion modeling influences future power system investment decisions. Greater renewable energy penetration has increased operational variability in power systems because renewable output is not fully controllable, requiring generators to respond to more dynamic conditions. Although the transitional behavior of thermal generators is often simplified in capacity expansion models, the variability introduced by renewable resources calls for an examination of whether this simplified representation remains adequate for accurate grid planning. To address this question, a deterministic mixed-integer linear programming model is developed that simultaneously solves capacity expansion, unit commitment, and economic dispatch problems to minimize the total cost of a small utility-scale power system over a 20-year planning horizon. A baseline model formulation with simplified start-up and shutdown representation is first constructed, followed by a detailed transition formulation that incorporates path-indexed, multi-hour start-up and shutdown trajectories for thermal generating technologies. Comparing the two formulations isolates the effect of increased transition resolution on investment decisions, dispatch outcomes, cycling behavior, carbon emissions, and total system cost. The results show that the detailed transition formulation remains broadly consistent enough to be a suitable substitute for the baseline model, but it produces meaningful differences in operational and planning outcomes. In particular, the baseline formulation appears to overstate thermal flexibility, underestimate operational friction, and distort the resulting investment portfolio when compared with the detailed formulation. Overall, the findings demonstrate that start-up and shutdown behavior is an important modeling choice in capacity expansion analysis, and that greater transition detail can improve the credibility of long-term power system planning results.

Antisense oligonucleotides (ASOs) are an established therapeutic modality with a growing preclinical pipeline. Translating a transcript into a viable ASO, however, requires more than sequence complementarity: mRNA folds into secondary and tertiary structures that render nominally complementary sites base-paired, buried, or only transiently accessible. Existing in silico tools capture secondary structure or single static three-dimensional folds but do not report time-dependent accessibility or binding behaviour in the presence of an ASO. This thesis develops a coarse-grained molecular dynamics (CGMD) pipeline that narrows these gaps. Target structures are obtained from the Protein Data Bank or predicted with NuFold and simulated in LAMMPS under the single-interaction-site (SIS) RNA force field of Nguyen, Hori, and Thirumalai [1] with the folding and binding implementation of Aierken and Joseph [2]. Candidate sites are identified by intersecting secondary-structure single-strandedness with per-residue solvent-accessible surface area, and ASO–RNA association is scored from the trajectory as a comparative apparent dissociation constant under a centre-of-mass distance framework. The pipeline is applied to a 1YMO-derived hTR pseudoknot hairpin and extended, without per-target retuning, to six additional PDB-derived RNAs. Across ten ASO variants at fixed loading, apparent Kd spans roughly an order of magnitude; extended-complementarity designs register the highest apparent Kd despite suppressing loop-core fluctuation most strongly, and both loop-core RMSF and apparent Kd depend non-monotonically on ASO loading. The integrated ranking reorders candidates relative to a complementarity-only shortlist—the pipeline’s principal contribution. Apparent Kd is reported as a comparative rather than an absolute quantity, several comparisons are single-replicate, and cross-target comparisons use differing binding criteria and box volumes; these caveats attach to the absolute values, not to the reordering itself.

Consolidated Bioprocessing (CBP) represents a promising platform for lignocellulosic biofuel production, yet its kinetic efficiency is fundamentally constrained by the structural recalcitrance of highly branched hemicellulose networks. To overcome these depolymerization bottlenecks, this study investigates the biochemical boundaries and cooperative dynamics of novel cellulosomal glycoside hydrolases derived from the thermophilic bacterium Acetivibrio thermocellus. Specifically, three distinct multi-modular architectures were selected for functional characterization: Clo1313 2857 (a GH43 10 α-L-arabinofuranosidase), Clo1313 2216 (a GH43 4 endo-α-1,5-L-arabinanase), and Clo1313 2795 (a multidomain GH30/GH43 20 construct). Recombinant targets were successfully expressed in Escherichia coli and isolated via immobilized metal affinity chromatography. Extensive profiling established isolated operating windows, with the GH43 catalytic cores exhibiting robust thermophilic activity between 60 ◦C and 70 ◦C at mildly acidic to neutral pH (5.0–7.0). Substrate specificity and depolymerization modalities were subsequently validated through colorimetric reducing-sugar assays and High-Performance Liquid Chromatography (HPLC). Clo1313 2857 demonstrated strict exo-debranching activity on wheat arabinoxylan (WAX), yielding exclusive L-arabinose monomers. Clo1313 2216 exhibited targeted endo-acting cleavage on sugar beet arabinan (SBA), accumulating higher-order oligosaccharide intermediates and displaying a pronounced non-linear kinetic lag phase at low enzyme concentrations (<0.015 μM). Building upon these isolated kinetic parameters, the cooperative dynamics of the hemicellulases were evaluated through systematic combinatorial screening. Combinatorial assays on SBA identified a highly active synergistic pairing between the endo-arabinanase Clo1313 2216 and the exo-acting AtAbf43C (Clo1313 2794), yielding a 1.91-fold increase in specific activity (U/mg). Further stoichiometric validation via the method of continuous variation defined a mathematically optimal 2 μmol Clo1313 2216: 3 μmol AtAbf43C formulation. Kinetic analysis confirmed that this synergy is driven by mechanistic compensation. The exo-enzyme cleaves the oligosaccharides generated by the endo-enzyme, alleviating the non-productive lag phase and yielding a 15-fold recovery in specific activity at low concentrations of Clo1313 2216. Ultimately, the precise biochemical characterization of these domains, coupled with empirical evidence of stoichiometric synergism, provides a foundation for engineering architectures necessary for robust monomer release during CBP fermentation.

In addition to the onslaught of environmental challenges posed by the warming climate, eutrophication is encouraging the growth of the cyanobacteria that cause harmful algal blooms (HABs) and release toxins that threaten human, wildlife, and environmental health. To track the emergence of and protect against cyanobacterial toxins, as well as to inform remediation processes, a robust and real-time detection system is first required. Here, I design, construct, and evaluate a sensor system that integrates Shewanella oneidensis’ naturally occurring extracellular electron transport (EET) pathways with nanobodies’ capacity for antigen-specific binding to digitize information on contamination events via a modulated electrical signal. This report outlines the expression, purification, and binding-capability assessment of the biological components for such a real-time bioelectronic detection device. In addition to creating a biohybrid device to detect microcystin-LR – a well-characterized cyanobacterial toxin within the microcystin family – I also designed a model system to detect green fluorescent protein (GFP) and validate the approach to cell-surface binding. The final design relied on the direct display of nanobodies on the surface of S. oneidensis for target detection. After confirming target binding to the cells via microscopy, I performed an electrochemical analysis of the sensor in response to target exposure. This preliminary study indicated that the engineered strain of Shewanella underpinning the sensor design demonstrates a change in current distinct from that of the control strain in both chronoamperometry and cyclic voltammetry experiments upon addition of the target.

The rhizosphere is a dynamic chemical environment shaped by secondary metabolites that influence microbial interactions, nutrient availability, and plant health. Among these, ribosomally synthesized, post-translationally modified peptides (RiPPs) represent a largely unexplored class of natural products. DUF692 multinuclear non-heme iron-dependent oxidative enzymes (MNIOs) are an emerging family of tailoring enzymes involved in the biosynthesis of RiPPs. These MNIO-modified RiPPs have shown growing evidence for roles in copper chelation, antivirulence functions, and microbial community dynamics, though their full potential remains underexplored. To address this gap, this study presents a scalable bioinformatic pipeline for identifying MNIO-associated biosynthetic gene clusters (BGCs) across bacterial genomes. Application of this framework uncovered over 1,200 putative MNIO-RiPP BGCs. To probe their functional relevance, we selected a candidate cluster from [Actinomadura] parvosata subsp. kistnae for experimental study. Mass spectrometry analysis revealed a unique mass shift consistent with MNIO-mediated modification, and a putative structure has been proposed. This work expands the known chemical space of MNIO-RiPPs and underscores their potential as bioactive mediators of rhizosphere interactions with translational relevance in environmental and agricultural contexts.

In the last century, rising atmospheric carbon dioxide (CO2) levels have demanded carbon removal technologies in addition to simple emissions cuts. Among these negative emission technologies is direct air capture (DAC), which extracts CO2 directly from ambient air. While DAC is a promising negative emission technology, it is limited by energy-intensive sorbent regeneration that typically involves high temperature or pressure swings. This limitation prompts interest in moisture-swing adsorption (MSA), which relies on changes in humidity to regenerate sorbent. In a moisture-swing DAC system, CO2 is adsorbed at low humidity and desorbed at high humidity. Tangentially, polyethylene terephthalate (PET) plastic is one of the most produced and under-recycled plastics globally, single-handedly contributing to both emissions and waste problems. This work proposes a chemical synthesis process to upcycle post-consumer PET bottles into a quaternary ammonium bicarbonate sorbent for moisture-swing DAC. Functionalization occurs via a four-step reaction sequence: aminolysis, Eschweiler-Clarke methylation, Menshutkin quaternization, and bicarbonate ion exchange. Successful conversion of the products is confirmed at each step via 1H NMR spectroscopy. The carbon capture performance of the upcycled PET-derived sorbent is then evaluated in the moisture-swing DAC system. The sorbent demonstrates reversible CO2 capture and release over five adsorption/desorption cycles. CO2 levels correlated directly with humidity swings from 35% relative humidity (dry) to 70% relative humidity (wet), consistent with the MSA mechanism. In addition, cyclical stability was observed with no measurable capacity loss. Thus, this research serves as a proof of concept for a negative emissions process that simultaneously addresses plastic waste and atmospheric CO2 mitigation.

Biomolecular condensates are an active area of research that offers tremendous promise, and research is helping to uncover their function in cellular biology and the potential for therapeutic intervention in pathological condensates. Experiments and simulations have led to continuous improvement in our understandings of biomolecular condensate thermodynamics, but the kinetic properties of condensation remain under-explored. In this project, we explore the nucleation properties of the intrinsically-disordered region (IDR) of human Ribonucleoprotein A1, also known as A1LCD. This protein’s thermodynamic properties are well-characterized by experimental studies, but its energetic barrier to nucleation is unknown. We propose a workflow to broadly resolve nucleation barriers for A1LCD from simulations alone, taking advantage of the Mpipi coarse-grained intrinsically disordered protein (IDP) model’s accuracy and performance to run microsecond-long simulations enabling the calculation of kinetic barriers to rare events. We make predictions of condensate nucleation barriers and correlate nucleation barrier height with known critical temperature values across six A1LCD mutants. We find that energetic barriers to nucleation are relatively constant across these mutant strains that condense at different critical temperatures, and additionally see that nucleation barriers rise as we approach the critical temperature for low system densities. In addition, we offer insights to future calculation of nucleation barriers for other IDPs.

Sustainable biofuels can be produced using agricultural feedstocks rich in lignocellulose, such as corn stalks and barley straw—low-cost, renewable feedstocks that are typically discarded. However, lignocellulose is both physically and chemically challenging to degrade. Anaerocellum bescii, a thermophilic bacterium that thrives at ~75°C, is a promising candidate for biorefining processes due to its powerful arsenal of carbohydrate-active enzymes (CAZymes), which can efficiently break down lignocellulose and convert it to ethanol and other biofuels. However, efforts to metabolically engineer A. bescii are hindered by a limited understanding of its ATP-binding cassette (ABC) sugar transport systems, which play a vital role in importing extracellular oligosaccharides into the cell. The Xylan Degradation Locus (XDL) and Conserved Xylan Utilization Locus (CXUL) are involved in xylose utilization and together encode three putative ABC sugar transporters. The XDL includes AxoFGE (Athe_0174–0176) and XloEFG (Athe_0179–0181), with Athe_0174 and Athe_0181 as the associated substrate binding proteins, while the CXUL gene cluster xynUVW (Athe_0614–0616) encodes Athe_0614. By heterologously expressing and purifying these proteins, followed by ligand screening using differential scanning calorimetry (DSC) and isothermal titration calorimetry (ITC), we identified their hemicellulosic sugar preferences and roles in transport. Additionally, ROSIE docking simulations, contact residue mapping, and sequence alignments with homologous proteins revealed conserved amino acids involved in xylo-oligosaccharide recognition. This work advances our understanding of how A. bescii utilizes diverse hemicellulosic substrates, accelerating its development as a platform for sustainable bioproduction of biofuels and other valuable chemicals.

Mesogens are molecules that can access anisotropic, liquid crystalline mesophases with useful optical, magnetic, and electronic properties. Mesogens with a bent shape have restricted rotational freedom along their long axis. Because of this restriction, these mesogens can form a range of low symmetry, smectic ‘Banana’ or ‘B-phases’. Also, under certain conditions, oligomers and dimers synthesized with flexible linkers can adopt a bent intermesogen geometry, allowing them to form B-phases as ‘flexible’ bent core mesogens. In rigid bent-core mesogens and dimers synthesized with a flexible linker, the formation of complex microstructures is triggered both by geometric frustrations from the packing arrangement and by a driving force to escape macroscopic polar order. These features give rise to assemblies with substantial curvature and sometimes supramolecular chirality, even in the absence of point chirality within the chemical structure of the mesogen. Because of their chirality, these specialized microstructures have drawn attention for their potential applications in synthesis and nanofabrication efforts in bio- sensors, optomechanics, and as templates for nanoparticle systems. This work examines the self-assembly of an achiral, asymmetric mesogenic heterodimer which is hypothesized to favor a bent intermesogen geometry. The heterodimer self-assembles into nanocylinders 128 ± 21 nm in diameter. Despite the achirality of the mesogenic subunits themselves, their hierarchical nanocylinder arrangement features planar chirality. To reveal the precise structure of the molecular assembly and affirm the potential of this system for further functionalization, copper-catalyzed azide-alkyne cycloaddition (CuAAC) fluorescent tagging procedures are used to visualize the placement of key functional groups within the nanocylinder assembly. We demonstrate that we can achieve a high degree of long-range order and alignment in the nanocylinder microstructure through seeded nucleation followed by slow, high-temperature isothermal crystallization. These findings explore methods to prescribe nucleation sites and direct the subsequent growth of the nanocylinder microstructures, which is an important step towards exploiting these cylindrical assemblies in device fabrication.

Electrolytic manganese dioxide (EMD) is a critical cathode material in lithium-ion battery technologies, requiring high-purity Mn(II) derived from manganese dioxide (MnO2) ores. Industrial production typically involves reducing Mn(IV) to Mn(II), followed by purification and electrochemical reoxidation. Conventional methods like reductive roasting or hydrogen peroxide leaching pose economic and environmental challenges. This study investigates ozone as an alternative leaching agent and benchmarks its performance against hydrogen peroxide. Synthetic EMD and manganeseenriched pyrolusite ore were suspended in sulfuric acid and treated with either hydrogen peroxide or ozone. UV-Vis and ICP-OES analyses tracked manganese speciation and dissolution over time. Hydrogen peroxide e↵ectively reduced Mn(IV) to Mn(II), with strong UV-Vis and ICP signals confirming dissolution. Ozone produced pink Mn(II)-like filtrates and transient Mn(VII)-like features, but ICP-OES data revealed lower net manganese concentrations, suggesting competing reoxidation or reprecipitation. Mechanistic evidence indicates ozone facilitates manganese dissolution via surface-mediated redox cycling involving reactive oxygen species, rather than acting as a direct reductant. Impurity e↵ects in natural ores further modulate redox balance. These findings highlight both the promise and complexity of ozone-mediated leaching and reinforce hydrogen peroxide’s e↵ectiveness as a benchmark for future process design.

This thesis investigates electrolytically driven calcium carbonate precipitation as a pathway for carbon dioxide mineralization through induced alkalization. Using a three-electrode setup with nickel foil as the working electrode, electrolysis of potassium bicarbonate solutions was conducted at controlled current densities to generate hydroxide ions via the hydrogen evolution reaction (HER). In-situ Raman spectroscopy was used to monitor interfacial speciation and quantify local pH near the electrode surface. Starting from an open-circuit pH of 8.35, the pH rose to 9.42 at two minutes and reached 10.83 after six minutes of electrolysis at −2 mA/cm2. Calcium carbonate precipitation experiments were conducted using solutions of sodium chloride and calcium chloride mimicking seawater concentrations. A key finding was that precipitation occurred primarily in the bulk of the solution, rather than directly at the electrode surface. This was confirmed by visual observations during electrolysis and supported by electrochemical impedance spectroscopy (EIS) measurements. While charge transfer resistance (Rct) remained high throughout, the relatively stable solution resistance (Rs) and increasing Warburg impedance over time indicated minimal surface blockage and a dominant role of diffusion-driven precipitation in solution. To further understand the precipitation process, Raman spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDXS) were used to characterize the solid calcium carbonate products. The predominant polymorphs identified were calcite and vaterite. SEM images showed that the crystals had well-defined morphologies, with spherical vaterite and rhombohedral calcite observed. Taken together, these results demonstrate the effectiveness of electrolytically driven alkalization for inducing carbonate formation and provide mechanistic insight into spatial precipitation behavior. The findings offer valuable direction for optimizing electrode and cell design in future electrochemical carbon capture systems.

Semicrystalline polymer networks were synthesized from a butadiene-derived cyclobutene oligomer (B4P1) via thiol-ene photopolymerization to investigate how crosslink density and curing temperature jointly control crystallinity and thermomechanical properties. Networks were formulated across four PETMP:B4P1 molar ratios (z = 0.1–0.4), yielding crosslink densities ranging from 1.25 to 5.00 B4P1 units per junction, and cured either at room temperature (25 °C) or above the networks’ melting point (120 °C). Gel fraction analysis confirmed that higher PETMP concentrations produced more complete network formation, while the lowest crosslinker ratio (z = 0.1) exhibited substantial swelling and network defects. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) revealed that increasing crosslink density increases both the glass transition temperature and thermal degradation onset, and that polymerizing the network at 120 °C significantly reduces crystallinity when compared to the room temperature synthesized networks. Dynamic mechanical analysis (DMA) demonstrated that room-temperature networks retain higher rubbery-plateau storage moduli, consistent with trapped crystalline reinforcement, and tan ω profiles suggest a broad crystal-to-rotator phase transition between 50–80 °C. Variable-temperature wide-angle X-ray scattering (VT-WAXS) corroborated the thermal melting behavior observed by DSC. Tensile testing confirmed that room temperature networks exhibit greater stiffness and yield strength, while heated networks display enhanced ductility at higher crosslink densities. Finally, preliminary shape memory experiments demonstrated repeatable thermal programming and recovery, establishing B4P1-based thiol-ene networks as a promising platform for stimuli-responsive smart materials.

The iron and steel industry accounts for a large proportion of fossil fuel consumption and carbon emissions. In total, 11% of the global carbon emission and 7-9% of the global greenhouse gas emissions is due to iron and steel production, and the average total emission of the steel sector is approximated to be around 3.7 bn tonnes of carbon dioxide per year for the last six years (Dollinger). Thus, an important project concerning the industry is finding modifications to the ironmaking and steelmaking process, either through alternative energy sources or new technology/process implementations, that would reduce the amount of carbon emitted into the atmosphere. An avenue that has/is being explored is process electrification, which redistributes the energy source of the process towards electricity as a prevalent source of energy. This has manifested itself into a greater shift towards a pathway called the “secondary steelmaking” or electric arc furnace (EAF) route. The EAF route uses electric arcs and chemical energy from fuel gas burners to heat up furnace charge. However, most of the carbon emissions that come out of the US iron and steelmaking industry are still produced from the “primary steelmaking” route, also known as the blast furnace - basic oxygen furnace (BF-BOF) route; 85% of steel emissions come from BF-BOF production, while 15% of come from EAF production (Evans). Thus, my independent research throughout the semester was to perform an in-depth literature review on the energy source breakdown of both pathways, and look at how the increase of electricity usage can provide an avenue for decarbonization through a cleaner electric grid. The total energies and flows were then encoded into Python, and different electric grid emission rates were tested to calculate the impact of cleaner grids on the total carbon emissions. Additionally, the distribution of steelmaking using the DRI-EAF pathway and the BF-BOF pathway was altered to look at the resulting benefits of prevalent electricity usage.

Chondroitinase ABC is an enzyme that has shown therapeutic potential in treating spinal cord injuries through the breakdown of glial scarring, which inhibits axonal regrowth. However, it is unstable at human body temperature, and has been difficult to stabilize, which makes it challenging to implement as a therapeutic. Thus, a collaboration between the Webb and Gormley labs identified and tested the ability of copolymers to serve as stabilizing agents. Many of these copolymers successfully boosted the retained enzyme activity (REA) of chABC over 24 hours at 310K, or human body temperature. However, the experiments involved in this study did not reveal the mechanism by which these copolymers endowed thermodynamic stability. If this mechanism of stabilization were better understood, it would contribute to the understanding of chABC’s thermal instabilities and forward the goal of implementing chABC as a therapeutic. Molecular dynamics simulations were utilized to computationally interpret the mechanism of copolymer stabilization of chABC. These simulations revealed that there are facets of chABC’s wet lab behavior that can be understood and interpreted computationally, as well as contribute to the understanding of copolymer chABC stabilization. Investigating the interactions between chABC and high REA copolymers revealed that high levels of intermolecular contact can lead to a maintained protein structure, while low REA copolymers can exhibit distinctly destabilizing behavior not exhibited in a laboratory setting. These impacts may be related to the ability of copolymers to block the collapse of chABC from a crescent into a torus. Successful blocking of destabilizing intra-protein interactions, along with high contact bracing, seems to result in the most successful stabilization of chABC. Conversely, blocking the destabilizing intra-protein interactions without any additional support results in the most significant destabilization of chABC.

This thesis establishes the fundamentals for designing a radiation shield and heat exchanger device for the Princeton Field-Reversed Configuration (PFRC) reactor. The device must capture neutron radiation, X-rays, and microwaves while effectively carrying heat out of the system using a coolant. Two design concepts were proposed: layered shell and packed bed. The thermal performance of a layered shell device was evaluated under varying flow rates and heat loads with a parametric study on design parameters, such as the number of cooling channels and the total coolant volume. Using numerical simulations, key performance metrics including maximum temperature and pressure drop were evaluated. For the layered shell, a nondimensional parameter Π is defined to represent the ratio of cooling capacity to thermal load. A logarithmic relationship between maximum temperature and Π is devised such that, given a maximum temperature limit, a critical value Π* can be calculated under which the system overheats. To start development on a packed bed design, a method was developed to randomly generate a slice of the packed bed which uses periodic boundaries and symmetry to represent a full bed. This method provides a starting point for CFD simulations to prepare for large-scale experiments. These findings provide insight into the design and optimization of a joint shielding and heat exchanger device, providing a basis for future improvements in swiftly designing and manufacturing an outer shell for the PFRC.

CRISPR-based diagnostics (CRISPR-Dx) are a growing technology for sensitive and specific nucleic acid detection without the accessibility restrictions of qPCR. However, there is currently no platform that achieves highly multiplexed CRISPR-Dx without the need for specialized equipment, preventing efficient deployment in point-of-care or point-of-need settings. Here, we make significant progress toward addressing this gap in the field: we design, develop, and test several iterations of a microfluidic chip capable of 10-plex CRISPR-Dx with lateral flow (LF) integrated for equipment-free result readout. We confirm the efficacy of our device in facilitating stop-and-start fluid flow and on-chip mixing in colorimetric flow control tests. To make our device compatible with biological diagnostics, we also develop novel processes for lyophilized reagent storage and post-reaction fluid dilution. We make strides toward the validation of our device and workflow in a CRISPRDx setting, successfully detecting synthetic tuberculosis (TB) and monkeypox (Mpox) DNA targets to achieve a new level of combined multiplexing and equipment-free accessibility in CRISPR-Dx.

H2 is a clean fuel that can circumvent the dispersed and intermittent nature of renewable energy sources, yet challenges in storing and transporting H2 restrict its current utilization. H2 can be converted to the more easily liquefied NH3 for distribution to its point of use where it is decomposed back to H2 sustainably via electrified processes, e.g., dielectric barrier discharge (DBD)-assisted reactors. Catalyst packed beds within the DBD can improve the low energy yields associated with these reactors by selectively facilitating surface reactions and interacting synergistically with the DBD. This thesis studies DBD-assisted NH3 decomposition with earth-abundant, inexpensive zeolites, as their ordered aluminosilicate nature and high dielectric constants are favored in DBD systems. Specifically, we probe zeolite elemental composition and pore structure effects on the H2 energy yield by systematically quantifying dilute NH3 decomposition rates and efficiencies within a single-stage, coaxial AC-powered reactor under similar experimental conditions in the presence of different zeolites. We systematically evaluate a suite of MFI-framework samples (X-MFI-Y, where X represents the cation (H+ or NH4+), and Y represents the Si/Al ratio (40 or 25)) as well as previously reported LTA (5A) and FAU (13X) frameworks. H-MFI-25 has higher steady-state decomposition rates and H2 energy yield than H-MFI-40, as well as the zeolite 13X benchmark. H-MFI-25 further has a higher H2 energy yield than the zeolite 5A benchmark, with a slightly lower but comparable steady-state decomposition rate. Steady-state decomposition rates on H-MFI-40 and H-MFI-25 trend logarithmically with NH3 feed concentration, similar to DBD-only reactions, yet the rates are higher in the presence of MFI zeolites at similar residence times. On average, steady-state DBD power is highest for the empty tube and lowest for H-MFI-25, while the inverse is true for H2 energy yield. H-MFI-25 further exhibits higher NH3 decomposition rates (0.41 μmol/s) and H2 energy yield (22 g/kWh) as well as a lower steady-state DBD power across feed concentrations compared to H-MFI-40. These results suggest that a lower Si/Al ratio (higher Al content) influences the bulk DBD properties, which could affect both the DBD-phase reaction rate as well as the DBD-zeolite interactions mediating the surface-facilitated reactions. Future deconvolution of zeolite and bulk DBD contributions to the decomposition rate is key for quantifying the overall surface-facilitated reaction kinetics and the underlying DBD-assisted mechanism of NH3 decomposition; this better understanding of the complex interactions in plasma-assisted chemistries is needed to overcome limiting efficiencies in sustainable green H2 production.