Chemical and Biological Engineering, 1931-2025

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.

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.

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.

Microtubules (MTs) are key components of the cytoskeleton and play a critical role in cell growth and division. During mitosis, the mitotic spindle, composed of dynamic MTs, acts as a structural framework that captures and segregates chromosomes into daughter cells. Although MTs begin assembling the spindle during prophase, the precise mechanisms initiating this process remain unclear. It is known that RCC1, the most upstream regulator of the Ran pathway, generates RanGTP to release spindle assembly factors that promote MT formation. However, the spatial and quantitative requirements for RCC1 in spindle assembly are still poorly understood. Given RCC1’s essential role in initiating this process, determining its minimum effective concentration and localization could provide important insights into how the spindle facilitates mitosis and where errors might arise. To investigate this, I used microfluidic devices to generate cell-like droplets encapsulating MTgenerating particles, allowing for precise titration of RCC1 concentrations. These devices were fabricated using the soft lithography method, where PDMS with the channel design was bonded to glass coverslips using plasma treatment. The encapsulated RCC1-coated particles facilitate the exchange of RanGDP for RanGTP, establishing a Ran gradient that drives MT formation and spindle assembly. Droplets were formed by injecting Xenopus egg extract as the aqueous phase and HFE-7500 oil as the oil phase. Xenopus egg extract is a cell-free system derived from frog eggs that preserves the biochemical machinery of cell division, making it an ideal model for studying MT dynamics in vitro. HFE-7500 is a fluorinated oil widely used in droplet microfluidics due to its chemical inertness, low solubility of aqueous components, and compatibility with surfactants that maintain droplet stability. My experiments revealed a power-law relationship between the volumetric flow rate ratio of the oil and egg extract and the resulting droplet sizes. Additionally, I observed that larger numbers of smaller RCC1-coated particles produced more complex MT network architectures around the self-localizing particles. To deepen our understanding of how RCC1 drives spindle formation, further experiments using varying concentrations of RanQ69L and RCC1 particles in microfluidic systems are needed.

Caldicellulosiruptor is a unique genus of bacteria that produces lignocellulose-degrading Carbohydrate Active enZymes (CAZymes). CAZymes are of particular interest because of their potential utility in processing cellulose for sustainable biofuel pathways. However, studying the CAZyme efficiently has been difficult both experimentally and computationally due to the enzyme’s large size, over 1700 amino acid residues in length. Previous computational studies have studied the CAZyme in a limited capacity, simulating only small sections of the protein with atomistic approaches. In this paper, I present Mpipi- Cellulose, the extension of the coarse-grained Mpipi force field to cellulose. Mpipi-Cellulose represents each monomer of cellulose as a single interaction site (or bead), allowing for more efficient computations yet still accurately capturing the cellulose-protein interactions of CAZyme binding to cellulose. Through a series of umbrella sampling simulations, potentials of mean force were constructed for interactions between cellulose and a variety of ligands, including peptide fragments and subdomains of CelA, the primary CAZyme produced by the Caldicellulosiruptor genus of bacteria. Mpipi-Cellulose demonstrated strong qualitative agreement with Martini3, a higher resolution coarse-grained model optimized for cellulose, across these simulations. Mpipi-Cellulose was then used to simulate the entire CelA interacting with a slab of crystalline cellulose. Using the newly developed model, I tracked the number of contacts between the enzyme and the cellulose, showing that the majority of the residues that interact with the cellulose come from the binding domains as predicted by experiments. Further simulations were performed with various CelA mutants, removing different binding domains and exploring the impact on interaction with the cellulose. These simulations demonstrated that the second and third binding domains in CelA are particularly important for proper binding to the cellulose surface. With this knowledge and further use of the Mpipi-Cellulose model, a wide number of mutants can be screened to optimize CAZyme performance for degradation of cellulose to produce biofuels.

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.

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.

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.

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.

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.

Biomolecular condensates present a compelling frontier in biological engineering due to their dynamic material properties and ability to spatially and temporally organize biochemical reactions without membrane boundaries. These structures form through liquid-liquid phase separation, a thermodynamically driven process in which proteins and RNAs spontaneously form reversible, concentrated droplets. Stress granules (SGs) are a class of condensates that self-assemble in response to cellular stress and play a critical role in the regulation of mRNA triage during translational arrest. However, aberrant SGs have been implicated in the progression of neurodegenerative diseases such as Alzheimer’s, frontotemporal lobar degeneration, and amyotrophic lateral sclerosis, where persistent SG assemblies are associated with the pathological aggregation of TDP-43. Despite the growing recognition of this correlation, the biophysical mechanisms that drive SGs toward disease-relevant states remain poorly understood. To address this knowledge gap, this thesis presents a coarse-grained, reaction-diffusion model that integrates phase separation theory and reaction kinetics to investigate SG formation and aging during different stress regimes. The model tracks the interplay between SG components, including mRNA and RNA-binding proteins, and aggregation-prone proteins such as TDP-43. By using numerical computing to systematically vary key biophysical parameters, including interaction strength, cytoplasmic mRNA levels, and mRNP dissolution rates, we simulate how SG morphology, domain size, and composition evolve over time. Our model provides a quantitative and mechanistic framework for exploring how SGs shift from functional condensates to sites for fibril formation, offering insights into the physical principles linking phase separation to protein aggregation in neurodegenerative diseases.

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.

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.

Bioelectrochemical systems (BESs) interface bacterial metabolic processes with electronic systems for purposes including biosensing, bioremediation, and modulating biological activity. A key bottleneck that currently hinders development of these systems is the difficulty of interfacing bacteria with electronics, resulting in the limited mutual transfer of charge associated with the contact between the bacteria's natural biofilms and an electrode surface. I developed a formulation using biocompatible conductive polymers and designed a device in which to electropolymerize an engineered living hydrogel that incorporates electrically active microbes into its polymer matrix, increasing the surface area contact between the bacteria and the electrode. With a connected potentiostat, the device allows for repeatable, consistent electrochemical systems for hydrogel synthesis and measurement via cyclic voltammetry and chronoamperometry. Engineering a new bridge between biology and electronics requires material that can syncretize the two worlds and an engineering design-build-test-learn cycle that can fine-tune this bridge to create a path toward more environmentally-friendly energy production in the future.

Biofuel development can serve as a possible approach to reduce GHG emissions and help mitigate the effects of climate change on the environment and human health. In the development of biofuels involving microorganisms, there have been various trade-offs between growth and ethanol production. While previous studies have proposed different approaches to assess these trade-offs, temperature-sensitive (ts) mutants have not been widely explored in this context. These mutants lack the function of a certain essential gene at nonpermissive temperatures and display full to partial function at semi-permissive temperatures. In this project, we performed screenings on a library collection consisting of 600 temperature-sensitive mutants of Saccharomyces cerevisiae essential genes at permissive (21°C) and nonpermissive temperatures (38°C). The aim is to identify strains that exhibit impaired growth at elevated temperatures, but can still maintain active metabolism to efficiently produce ethanol. This is based on the assumption that high temperatures can disrupt cellular processes and functions linked to growth, but not ethanol fermentation because of the changes in metabolic pathways. Initial screenings were conducted using alcohol dehydrogenase assays, and high-performance liquid chromatography was used to verify the high specific production ratios of 15 ts mutants that were selected. The gene ontology analysis confirmed that many of these selected genes are involved in growth-related processes, such as cell cycle regulation and ribosomal biogenesis. Further work should be conducted to dynamically control these strains using optogenetic techniques to improve the fermentation efficiency. Additional experiments should also investigate whether these ts alleles can produce more ethanol than the wild-type (BY4741) through fed-batch fermentations.

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.

The ability to spatially control the presentation of proteins on substrates is essential for investigating cellular responses to microenvironmental cues and for engineering functional biomaterials. This paper reviews and compares several protein patterning techniques, including photopatterning using quartz photomasks, digital micromirror devices (DMDs), microcontact stamping, and patterning with stencils. Each method is evaluated based on its throughput, accessibility, and suitability for generating both defined patterns. Each method was tested experimentally, and it was found that the cells were able to adhere onto substrates regardless of where the protein patterns were created for techniques that used Poly-L-lysine polyethylene glycol (PLL-g-PEG). In order to more reliably control the protein pattern and cell adhesion, physical barriers such as silicone stencils were also used to dictate the protein patterning. This allowed for easy and reliable control over the protein patterns, which enabled the electrotaxis experiment that was conducted. The protein patterned substrates are used to control the shape and size of cells to study the effect of tissue size on the response of the tissue when placed in an electric field. We found that increasing tissue size leads to an increase in the velocity of the cells along the direction of the stimulation direction, and we provide several explanations for why this phenomenon is observed.

Mismanagement of plastic waste presents significant environmental challenges, with only a small fraction of plastic being recycled and a majority ending in landfills or natural environments. To address these concerns, this study explores catalytic upcycling of polyolefin plastics using hierarchical FAU-type zeolite catalysts. Specifically, it investigates how mesoporous structures within FAU catalysts influence catalytic cracking performance, which is essential for converting bulky plastic polymers into economically valuable hydrocarbons. Four distinct hierarchical FAU materials were synthesized via varied post-synthetic desilication methods, each generating unique mesoporous networks characterized through X-ray diffraction, N2-physisorption, and acidity measurements via temperature-programmed desorption. Catalytic cracking reactions of polyethylene (PE), polypropylene (PP), and hexatriacontane (C36) were conducted to evaluate performance differences attributable to mesopore size, volume, and connectivity. Results revealed significant improvements in cracking rates for catalysts synthesized with surfactants (H-FAU-CTA, H-FAU-TPA), while hydrothermally treated catalysts showed enhanced reactivity specifically for larger, branched PP molecules, suggesting that mesopore accessibility and geometry significantly modulate catalytic efficacy. Importantly, the presence of mesopores alone did not universally enhance reaction rates; instead, performance depended critically on mesopore characteristics and reactant molecular size. These findings demonstrate the nuanced relationship between hierarchical porosity and catalytic activity, emphasizing the importance of targeted mesopore design for optimizing plastic waste upcycling processes. The insights gained lay foundational knowledge for developing advanced catalysts that could significantly improve environmental sustainability and facilitate a circular economy for plastics.

Global agricultural production must increase by up to 70% by 2050 to meet the demands of a growing population (1). Sustainable agriculture, harnessing the power of naturally occurring plant-associated microbes, offers a promising way to improve agricultural productivity. Optimizing the performance of beneficial microbes will require a deeper understanding of how these bacteria colonize roots and interact with the plant immune system. Traditional tools for microbial tracking such as 16S rRNA sequencing, fluorescence markers, or antibiotic resistance are often limited by resolution, bias, and poor compatibility with soil environments (17-19). This study applies Wild-Type Isogenic Standardized Hybrid (WISH) tagging, a novel microbial barcoding technique developed by Daniel et al. (2024), to track and quantify root colonization dynamics with (20). In this study, WISH tags were inserted into the following bacterial strains: Pseudomonas simiae WCS417, Dyella japonica MF79 wildtype, and its mutant, a knockout of the immunosuppressive subtilase A (IssA) gene. Sequencing of WISH-tagged populations revealed a competitive advantage of the ΔIssA mutant over the wild-type, indicating that immune suppression traits may incur fitness trade-offs. Overall, this work demonstrates the power of WISH-tagging for high-resolution analysis of plant–microbe interactions and underscores its potential as a tool for future microbiome engineering and sustainable agricultural innovation.