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.

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.

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.

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.

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.

Plant root exudates shape the structure and function of the rhizosphere microbiome by providing chemical cues and substrates that influence microbial survival, colonization, and interaction with the host. These exudates can select for beneficial microbes that support plant growth or suppress immunity, making them critical in mediating plant-microbe interactions. This study focuses on two Arabidopsis thaliana (Arabidopsis) associated, immunity-suppressive bacterial strains, Dyella japonica MF79 (MF79) and Brevundimonas sp. MF374 (MF374), which use distinct genetic mechanisms to suppress root immune responses. To evaluate how the root exudate composition influences bacterial fitness, transposon mutant libraries of MF374 and MF79 were grown in exudates derived from Arabidopsis Col-0, fls2 mutant, and cyp79b2/b3 mutant lines. Genome-wide fitness profiling using random barcode transposon-site sequencing (RB-TnSeq) and Random Forest classification revealed minimal fitness changes in response to flg22 treatment, but strong genotype-specific fitness differences driven by root exudate composition. In MF374, candidate genes involved in osmotic regulation, cell wall synthesis, oxidative stress response, and translation were identified as major contributors to fitness in root exudate environments. Targeted gene deletions confirmed reduced fitness in immune-active or metabolite-rich exudates; however, root colonization assays demonstrated that these fitness effects did not always translate to differences in colonization capacity. This framework enabled the identification and functional assessment of bacterial genes important for exudate-mediated fitness and adaptation. The findings offer insight into how variation in root exudate composition influences the assembly, persistence, and adaptation of immunity-suppressive bacteria within the root microbiome and have broad implications for understanding plant health and developing strategies for microbiome-based agricultural applications.

This thesis proposes a model for the effects of YAP signaling on Sox2 and Sox9 expression and lung morphology during the E12 stage of branching morphogenesis in mouse lungs. Results of culturing experiments demonstrate that inhibiting YAP causes growth of the epithelium into cystic structures rather than distinct branches. Results of immunostaining experiments suggest that YAP constrains Sox2 and Sox9 to the airway epithelium, and that inhibiting YAP allows expansion of Sox2 and Sox9 expression into the mesenchyme, which leads to abnormal branching morphogenesis. Results of qPCR experiments provide quantitative confirmation that YAP inhibition causes additional expression of Sox2 and Sox9. Together, these results suggest that normal branching morphogenesis requires the absence of Sox2 and Sox9 expression in the mesenchyme to promote smooth muscle wrapping. Future research should examine YAP signaling at stages of development before and after E12, study different downstream proteins of the YAP signaling pathway, and use other experimental techniques to separately quantify protein expression in the epithelium and in the mesenchyme. This research has important implications for engineering of complex branched lung tissues to treat lung diseases.

Understanding how antibiotics affect bacterial cells beyond their primary target is essential for developing next-generation therapeutics. Traditional profiling methods primarily focus on identifying a drug’s direct target, often overlooking the downstream cellular effects of antibiotic treatment. This study evaluates a modified Bacterial Cytological Profiling (BCP) approach that uses a panel of Escherichia coli mutants with deletions in transcription-associated genes to characterize antibiotic mechanisms of action beyond their primary target. By integrating GFP-based translational readouts with measurements of DNA content (DAPI), membrane structure (FM4-64FX), and cell size (FSC), analyzed via flow cytometry, we examined cellular responses to two transcription-blocking rifamycins: rifampicin (RIF) and rifabutin (RFB).

We found that many mutants exhibited consistent and gene-specific cytological responses to RIF, highlighting the method’s ability to reveal downstream effects of RNAP inhibition. Additionally, drug-specific phenotypes emerged between RIF and RFB, demonstrating that the modified BCP approach can resolve subtle mechanistic differences between closely related antibiotics.

Together, these findings validate the modified BCP approach as a tool for uncov- ering antibiotic action with greater depth and resolution, offering valuable insights for future drug development.

Förster resonance energy transfer (FRET) is a spectroscopy technique that measures energy transfer between acceptor and donor compounds attached to biological molecules. It is a convenient metric for distance measurement on the angstrom scale. Theoretically, this process could be applied to DNA mixtures to identify key components in a variety of applications, such as pathogen detection in crops. The uncertainty inherent in the use of the procedure for identification must be overcome with a similarly stochastic process. This work presents a foundational dataset which serves as a proof-of-concept for the potential to create an unsupervised model that could be used to determine whether detectable patterns arise from FRET efficiency sampling of such mixtures. A coarse-grained DNA model is selected for compatibility with relevant protein models and close approximation of realistic datasets. Through CMA-ES performed on MD simulations of twelve batches of potential acceptor probes that seek to select for interaction with one genome of interest, a basis for synthetic data generation is achieved. Analysis shows that significant changes to the fitness of probes for selectivity of interaction with a specific DNA mixture can occur, showcasing that extraction of patterned information from a synthetic FRET profile for the purpose of mixture identification is plausible. This work provides insight into how machine learning models can be used for the characterization and identification of unknown DNA sequence mixtures while also furthering the advancement of such analysis in dynamic environmental systems like what can be found in field conditions.

Genome mining methodologies were used to advance three high impact projects. In project 1, homology-based genome mining was used to discover a new thermostable poly(ethylene terephthalate) (PET)-degrading enzyme. Rational engineering aided by structural modeling was then used to improve enzyme activity. In project 2, a custom genome mining script was used to discover 1094 examples of lasso pep- tides with putative anti-cyanobacterial activity. These lasso peptides are examples of RiPPs—ribosomally synthesized and post-translationally modified peptides—and contain a unique lariat-like knot. In the 1094 anti-cyanobacterial examples, the lasso peptides likely bind a critical metal needed by cyanobacterial metabolism, after which the metal-lasso complex is imported by the lasso-producing organism and linearized via an isopeptidase. The presence of this isopeptidase gene was used to find the anti-cyanobacterial lasso peptides. Project 3 also involved RiPPs; typically, RiPPs use one class defining enzyme to install a modification onto a ribosomally synthesized peptide precursor. To expand the range of chemistries observed in nature, large-scale genome mining and bioinformatic analysis was used to identify the first examples of hybrid RiPPs, which putatively employ more than one class-defining enzyme to create unique structures. The first examples of hybrid RiPPs were heterologously expressed and purified in E. coli. Nomenclature for these new molecules was created after further bioinformatic exploration of several dozen other putative hybrid RiPPs. The successful computational and experimental workflows used to identify and syn- thesize the first hybrid RiPPs can be applied to find more hybrid RiPPs with unique structures and applications in natural product-based pharmaceuticals.

Biomolecular condensates are membraneless organelles inside living cells that primarily comprise proteins and nucleic acids. The thermodynamic process of liquid-liquid phase separation has been proposed as a primary driver of biomolecular condensation, and it is recognized that phase separation is maintained by networks of biomolecular interactions within these liquid droplets. Canonical examples of condensing biomolecules include prion-like low-complexity domains (LCDs) of proteins, and simulations of single-component LCD condensates have predicted the presence of small-world topologies in the interaction networks underlying condensate stability. Recent experimental and theoretical works have also demonstrated inhomogeneities in single-molecule conformation, orientation, and dynamics within biomolecular condensates. Here, we systematically characterize the molecular networks underlying both LCD condensates and condensates formed by generic associative heteropolymers. Further, we investigate the relationship between network topologies and single-molecule properties within condensates. To probe LCD condensates, we employ a chemically specific, coarse-grained model of disordered proteins designed to reproduce phase separation statistics. We generalize our findings by varying sequence hydrophobicities using a generic binary model of associative heteropolymers, dubbed the “hydrophobic–polar” (HP) model. In both model systems, we find persistent small-world topologies underlying single-component condensates. These topologies feature molecular “hubs” with high network betweenness centrality and molecular “cliques” that represent densely interacting clusters of biomolecules; distal cliques in condensate volumes all localize to phase interfaces and are bridged by elongated hubs that remain near condensate centers. Strikingly, we find that relationships between network connectivity and biomolecular structure and dynamics are governed by power laws. Our work demonstrates that inhomogeneous single-molecule behaviors within biomolecular condensates can be well predicted from condensate network connectivities. Furthermore, we find that network cliques have substantially longer lifetimes than molecular hubs, and that the motion of molecules within cliques is spatially constrained. Together, these results reveal a dynamic hub-clique architecture underlying condensates and suggest that the physicochemical characteristics and material properties of phase interfaces are critical to pathological gelation and fibrillization processes observed in condensate aging.

Intrinsically disordered proteins are key components of many liquid-like biomolecular condensates that are thought to contribute to a broad range of cellular functions, including mRNA processing, stress responses, and signal transduction. These same proteins also form pathological aggregates which are hallmarks of neurodegenerative diseases. However, how the same components exist in both material states in vivo remain poorly understood. To investigate how a liquid-like and arrested assembly might coexist within the cell, this work utilized Forever Corelets, a constitutive 24-mer oligomer, as a model arrested assembly. Comparing to its liquid-like, light-induced counterpart the Corelet system, we investigated how tuning homotypic interaction strength, phosphorylation state, and valence influenced the phase coexistence behavior of these engineered oligomeric constructs through mutations that perturb self interaction strength and mimic endogenous phosphorylation, as well as by modulating the fixed valence of the Forever Corelets oligomeric core. Particle tracking of individual puncta throughout the course of hypotonic dissolution treatments performed on the various populations revealed that the Forever Corelets display two kinetically distinct populations: a rapidly dissolving reversible phase and a persistent arrested phase. Decreasing homotypic interaction strength and increasing phosphomimic content rendered the Corelets populations more susceptible to hypotonic dissolution, in line with previous work that has shown that those specific biophysical manipulations decrease the propensity of the system to phase separate. Applied to the Forever Corelets, these manipulations decreased the clustering propensity of the assemblies and increased the fraction of assemblies resistant to hypotonic dissolution. However, increasing the valence of the Forever Corelets did increase the irreversibility of the system, pointing to valence as a universal driver of assembly formation regardless of the formation paradigm. Together, these data establish the Forever Corelets system as a model system for studying liquid-arrested phase coexistence within the cell. Additionally, this work establishes how valence, transient interaction energy, and electrostatic repulsion can modulate the phase coexistence behavior of the Forever Corelets system. This framework may offer insight into the phase behavior of native condensates, inform design principles for multiphase synthetic organelles, and work to clarify the role of liquid-arrested phase coexistence in driving pathological aggregation in neurodegenerative diseases.

Agricultural systems around the world are using increasingly large amounts of nitrogen, phosphate, and potassium synthetic fertilizers to support modern-day demands. Unfortunately, these fertilizers contribute to greenhouse gas emissions and wash off into natural waterways, posing environmental harm. Climate change further exacerbates the stresses on agricultural systems, leaving them susceptible to crop disease and reduced productivity. A consequence of excessive synthetic fertilizer use and climate change stress is plant nutrient imbalance. Nutrients are essential for a variety of necessary functions; without them, the plant will face stunted growth, low yield production, and other negative side effects. While the Earth’s soil is abundant in nutrients, most of them are bound in soil minerals. Geochemical release processes like mineral weathering are very slow, but minerals can also be processed for plant uptake via microbial mineralization mechanisms. Rhizospheric microbes play a crucial role in making nutrients available for plant uptake. Nitrogen-fixing, phosphate-solubilizing, and potassium-solubilizing bacteria are essential in making these macronutrients bioavailable to support plant growth. This project sought to uncover the potassium-solubilizing bacteria (KSB) within the Arabidopsis and Brachypodium root-microbiome and elucidate the key genes and mechanisms that these KSB employ to make nutrients available for plant uptake. Furthermore, using transposon mutagenesis, this project constructed a mutant library of a select strain, Rhizobacterium sp. PA090, to further investigate the KSB genome. This work will be used to inform further research and guide the development of biofertilizers as a sustainable alternative to the environmentally harmful chemical fertilizers.

This research explores the structural and catalytic implications of using melamine cyanurate (MCA), a supramolecular hydrogen-bonded framework, as a novel support material for heterogeneous palladium catalysts. Palladium nanoparticles were supported on MCA using both sol immobilization and impregnation–reduction methods, with additional samples incorporating a sulfur-containing ligand (MTT) to probe surface interactions. Structural, compositional, and morphological analyses were performed using XRD, XPS, TEM, and TGA. Catalyst performance was assessed using the Suzuki–Miyaura cross-coupling reaction. While palladium was successfully incorporated with small particle sizes, MCA-supported catalysts demonstrated low catalytic activity and significant evidence of support degradation under basic reaction conditions. These findings suggest that while MCA offers favorable nanoparticle dispersion and tunability, its structural instability under certain conditions limits its application as a robust catalyst support. Further optimization of reaction conditions and support modifications are proposed to improve its viability.

This study investigates the effect of nozzle geometry on flow-induced nanostructure alignment in a 50 wt% Pluronic 84 and water solution using birefringence imaging. The original objective was to evaluate alignment behavior in SEBS (styrene-ethylene-butylene-styrene) block copolymers under 3D printing conditions. However, mechanical failure of the 3D-printed nozzles—cracking under the high pressures— necessitated a pivot in material and methodology. Pluronic 84 was selected as a model system. Two nozzle geometries—a conical and a hyperbolic profile—were evaluated across a wide range of flow rates. While the hyperbolic nozzle was expected to induce greater alignment due to smoother extensional flow, both geometries produced comparable alignment levels. This suggests that the highly structured and viscoelastic nature of the Pluronic gel may limit further alignment regardless of flow profile. Instabilities observed in the birefringence images, potentially caused by elastic flow behavior or sample inhomogeneities were further investigated using non-polarized imaging. These findings highlight the interplay between flow geometry and material properties in directing nanostructure orientation. Future work will revisit SEBS with stronger nozzle materials and explore a wider range of pluronic concentrations, and nozzle geometries.