Liquid Phase Deposition of Nickel Oxide as a Hole Transport Layer for TEMPO-Mediated Oxidation

Favor Igwilo, Texas Christian University, Class of 2026
Laboratory of Dr. Benjamin Sherman, PhD;
Department of Chemistry and Biochemistry

Efficient positive charge (hole) transport is essential in photoelectrochemical systems for driving oxidation reactions. In our target process, 2,2,6,6-tetramethylpiperidin-1-oxyl (TEMPO), a stable free radical mediator, drives the redox reaction of benzyl alcohol to benzaldehyde, a reaction with significant applications in industrial processes and synthetic chemistry. TEMPO-mediated oxidation offers a sustainable alternative to conventional oxidation methods that generate hazardous waste, highlighting the need to enhance its viability in photoelectrochemical applications. Nickel oxide (NiO), a p-type semiconductor, is suited for this role due to its hole transport ability, abundance and cost-effectiveness compared to conventional alternatives such as TiO₂. To integrate NiO as a hole transport layer in TEMPO-mediated oxidation, we developed a liquid phase deposition (LPD) protocol for fabricating uniform NiO films on fluorine-doped tin oxide (FTO) glass. These films were incorporated into FTO|WO3-BiVO4 photoanodes to improve charge separation and hole extraction under light conditions.

Our experiments indicates that the uniformity and quality of NiO films are affected by deposition parameters, including the pH of the boric acid (H₃BO₃) solution, the type of base employed for pH adjustment (NH₄OH vs. NaOH)), and the temperature of nickel(II) fluoride tetrahydrate (NiF₂·4H₂O) to H₃BO₃ precursors. Characterization by profilometry reveals that maintaining a pH between 7.5 and 8 consistently produces uniform films with thicknesses in the range of 100–200 nm. UV–Vis spectroscopic analysis confirms the expected optical absorption of NiO in the near-ultraviolet region, while further electrochemical characterizations via cyclic voltammetry and chronoamperometry will further assess hole transport efficiency. This work establishes a scalable approach for NiO film fabrication that will enhance the performance of WO₃–BiVO₄ photoanodes in TEMPO-mediated oxidation processes, advancing sustainable, solar-driven alcohol oxidation with reduced environmental impact.

Emma Kulla, ¹Emily Rathke, ¹Braden Chadwick, Shauna M McGillivray, and Jean-Luc Montchamp*

¹Contributed equally

"Synthesis of Penicillin G Prodrugs and Assessment of Antibiotic Activity"

ABSTRACT
The goal of our project is to synthesize and evaluate prodrugs for phosphorus-containing antibiotics. To begin, we evaluated common prodrug moieties. This is because the preparation of phosphorus prodrugs is significantly more complex than that of carboxylic acids. In an attempt at determining the best prodrug moieties or at least establish if there are significant differences among the various bacterial strains, a series of compounds was synthesized. Penicillin G (potassium salt) was chosen as the model compound since it is a well-established antibiotic, and since there is only a carboxylate group needing derivatization. The potassium salt of penicillin G (PenCOOK) was esterified directly to PenCOOR by alkylation in DMF. The following R groups have been prepared: CH₂OC(O)t-Bu, CH₂C₆H₄(4-OAc), CH₂C₆H₄(4-NO₂), and CH₂C₆H₅. The former two compounds should be triggered by bacterial esterases, whereas the nitrobenzyl ester should be triggered by bacterial nitrogenases. The benzyl ester provides a control for the para-substituted benzyl derivatives. These compounds were then tested against the gram-positive pathogen, Bacillus anthracis Sterne. We find that the minimum inhibitor concentration (MIC) of the control (non-derivatized) penicillin-G was 120 μM (approximately 40 μg/ml), which is consistent with our previous studies. The addition of the prodrug moieties substantially increased the effectiveness of penicillin for all 4 pro-drugs. This result was most striking with EK31 (R = CH₂OC(O)t-Bu), which lowered the MIC to 3.75 μM (1.25 μg/ml). These results may be confounded by the lack of solubility of these prodrugs in aqueous media as EK31 also had the best solubility of the prodrugs tested. Future experiments will be needed to address this challenge and optimize the prodrugs, but our results indicate this is an effective approach.

Oxidative stress through the production of reactive oxygen species (ROS) has been shown to damage molecules in the brain and lead to the neuronal damage characteristic of AD. Additionally, metal ions like iron, copper, and zinc have been shown to not only bind to amyloid beta proteins and induce their aggregation, one hallmark of AD, but these metals also stimulate the production of ROS. To effectively fight AD, therapeutics should not only be able to chelate these metals and reduce oxidative stress but also prevent the aggregation of amyloid beta proteins. The Green Lab has produced ligands that both effectively chelate metals and reduce oxidative stress through interacting with ROS, but these ligands simply prevent the progression of the disease without affecting amyloid-beta protein aggregation directly. In this presentation, a synthetic scheme is proposed for the creation of a Green Lab ligand with the KLVFF peptide attached. The KLVFF peptide in the past has been shown to prevent amyloid-beta plaques from aggregating in vitro. Additionally, research has also been done showing that KLVFF, when attached to nanoparticles, can pass through RAGE receptors that are produced in the brains of AD patients. Through the addition of this peptide to the ligand, a small molecule that can chelate transition metals, reduce the effects of ROS, and prevent amyloid-beta aggregation will have been synthesized, providing a potential new therapeutic solution for Alzheimer's Disease treatment.

Salt-induced diffusiophoresis is the migration of a charged nanoparticle in water, induced by an imposed directional gradient of salt concentration. This transport phenomenon has emerged as a valuable tool for particle manipulation inside porous materials and microfluidics. Micelles represent a common example of nanoparticles with the crucial ability of hosting small guest molecules. Thus, micelle diffusiophoresis is important in the manipulation of small molecules. Micelle diffusiophoresis depends on micelle Brownian mobility or diffusion coefficient. This transport parameter describes the intrinsic ability of a micelle to randomly move (diffuse) in water. The poster reports diffusion-coefficient measurements carried out on aqueous solutions of the surfactant, hexadecylpyridinium chloride (CPC), in the presence of aqueous NaCl by dynamic light scattering. The effect of surfactant and salt concentrations on the diffusion coefficient of CPC micelles is discussed. These data are used to characterize salt-induced diffusiophoresis of charged micelles.

In this work, a single-layer tungsten oxide (WO₃) film on fluorine-doped tin oxide (FTO) coated glass was successfully prepared by the dip-coating method, followed by thermal treatment at 450°C. The structure and electrochemical properties of the WO₃ film were then determined via UV-Vis spectroscopy, IR absorption, surface profilometry, and XRD analysis. The result suggests that the films have consistent thickness and uniformity, with future investigations needed to explore how they interact with the addition of a nickel oxide layer and bismuth vanadate layer determined by electrochemical measurements such as cyclic voltammetry, chronoamperometry under light and dark conditions. WO₃ electrode can be used as the base layer to make FTO-WO₃-Bismuth Van(BiVO₄)-Nickel Oxide (NiO) electrode ,which has the potential to improve the photochemical performance in photoelectrochemical cells.

Copper plays particularly important roles in tumor growth and metastasis, making it a new target for anti-cancer therapies. The goal of this project is to exploit the pathways that cancer uses for proliferation as a target to inhibit cancer cell growth. To achieve this, tetra-aza macrocyclic small molecules will be used to sequester copper from the copper metabolizing pathways, recently we have discovered these molecules have high affinity for copper, water solubility, low toxicity, available in gram-quantities, and well-characterized. Our lead compound will be evaluated for anticancer activity on normal and breast cancer cells. This project also seeks to examine the pharmacological properties of the lead compound and explore of our compound on cooper pathways that leads to oxidative stress and inflammation.

Density Functional Theory (DFT) is a method for simulating molecules by approximating their electron densities, with various functionals available to model these systems. M11plus is one such functional, a range-separated hybrid meta functional that combines long-range non-local Hartree–Fock exchange with the non-local Rung 3.5 correlation, which has demonstrated effectiveness across a broad range of chemical databases. This work implements the M11plus functional into the PySCF open-source Python library and reparametrizes necessary fitting constants.

Silicon is a fundamental material in modern technology, with common applications including solar panels and numerous electronic devices. While high-purity silicon is necessary for these industries to ensure optimal electrical properties, biomedical applications such as drug delivery can tolerate alternative synthetic methods that prioritize sustainability and cost-effectiveness. This research focuses on developing an environmentally friendly approach to producing high-surface-area porous silicon using self-propagating high-temperature synthesis (SHS). This method utilizes silicon dioxide (SiO₂) as the silicon source, magnesium (Mg) as a reducing agent, and sodium chloride (NaCl) as a reaction moderator. The exothermic reaction between SiO₂ and Mg rapidly generates the heat necessary to facilitate silicon production, while NaCl helps regulate temperature, maintain porosity, and control grain growth. Unlike traditional silicon production processes that require high thermal energy input and costly purification steps, this SHS-based approach is designed to be scalable and accessible, particularly in resource-limited settings.
In a typical reaction, the Mg and SiO₂ reactants are exposed to a finite voltage (~12V) for a fixed amount of time (minutes) to initiate the reaction. After synthesis, the crude silicon product undergoes purification by dissolving the magnesium oxide (MgO) byproduct in hydrochloric acid, leaving behind high-purity silicon. This study aims to optimize reaction parameters (magnitude of voltage and duration) to maximize silicon yield and structural integrity while minimizing environmental impact. X-ray powder diffraction (XRD) is employed as the primary characterization technique to evaluate crystallinity and purity. The combination of a low-energy, cost-effective synthesis process and naturally derived raw materials positions this method as a promising green alternative for producing porous silicon. Its potential for drug delivery applications, particularly in developing regions with limited access to advanced manufacturing infrastructure, further underscores its significance in the field of biomaterials and sustainable materials science.

Salt-induced diffusiophoresis is the movement of a charged nanoparticle in water, driven by an imposed directional gradient of salt concentration. This transport phenomenon has become a valuable tool for manipulating charged nanoparticles within porous materials and microfluidic systems. Micelles are a typical example of nanoparticles with the important ability to host small guest molecules. Therefore, micelle diffusiophoresis is also crucial for manipulating small molecules. This poster reports measurements of diffusiophoresis coefficients carried out on aqueous mixtures of the surfactant, hexadecylpyridinium chloride (CPC) in the presence of NaCl by Rayleigh interferometry. Measurements of NaCl osmotic diffusion from high to low micelle concentration are also reported. We observe that diffusiophoresis of CPC cationic micelles occurs from high to low salt concentration. A model describing the behavior of micelle diffusiophoresis as a function of NaCl concentration is reported. Our diffusiophoresis results are explained in terms of micelle electrical charge, salt osmotic diffusion coefficients and zeta potential. This work offers new insights into diffusiophoresis of charged nanoparticles with potential applications for enhanced-oil recovery from porous rocks, soil remediation and diffusion-based mixing inside microfluidics.

The development of cerium oxide (CeO2) nanomaterials is rapidly advancing, driven by their wide range of applications in catalytic converters, solid oxide fuel cells, and biological sensors. Considering this, doping CeO2 with rare earth elements such as Europium (Eu3+) not only enhances its catalytic properties but also adds visible fluorescence to the list. To explore the variability of this effect, Eu3+ doped CeO2 nanotubes were synthesized and carefully analyzed by varying the Eu3+ concentration to investigate their optical properties, crystallinity, and morphology. Current research is focused on evaluating the potential of these doped CeO2 nanotubes as probes for bioimaging and optical sensors.

Reactive oxygen species (ROS) are byproducts of normal cellular metabolism. While essential in cell signaling and immune responses, unregulated or chronic levels of elevated ROS can cause oxidative stress. If this occurs in the brain, oxidative stress can lead to irreversible damage of macromolecular structures, including neuronal cell damage. Excessive ROS species are a hallmark of Alzheimer’s Disease (AD) and other neurodegenerative disorders. Superoxide dismutase (SOD) enzymes serve as a critical defense mechanism against ROS but have been found in lower concentrations in individuals with neurodegenerative disease. As a result, water-soluble small molecules that can mimic the SOD1 activity are of great interest to controlling diseases derived from oxidative stress. Herein, we present the SOD mimic activity for a library of copper tetra-aza macrocyclic small molecules and compare it to the most active congeners reported to date.

Texas is home to significant mining activity, both for oil and gas but also for other industrially useful materials. One such material is calcium carbonate. The chemical instrumentation course was contacted by a local mining company interested in analysis of soil samples from potential drilling locations, specifically determining calcium content and the presence of hydrocarbons. Over the course of the semester, the students in chemical instrumentation have analyzed four separate soil samples for both calcium content and various hydrocarbons using multiple instruments in the chemistry department including atomic absorption spectroscopy, infrared sprectroscopy, GCMS, thermogravimetric analysis, and NMR. We determined that calcium is present in the soil samples in concentrations up to 5% by mass, and that some hydrocarbons are present.

Photoelectrochemical (PEC) systems can be used to harness solar energy to drive sustainable oxidations reactions, such as those mediated by TEMPO ( 2,2,6,6-tetrameth-ylpiperidinyl-N-oxyl), a stable radical with applications in organic synthesis. This work focuses on preparing bismuth vanadate (BiVO4) films for multilayer electrodes (FTO|WO3-BiVO4-NiO) to enable PEC TEMPO oxidation studies. Double-layered BiVO4 films were fabricated on fluorine-doped tin oxide (FTO) substrates through dip-coating and a subsequent thermal treatment at 450°C. Various means of optimizing film performance and quality were explored, including precursor stoichiometry, dipping frequency, and drying conditions.

Our experiments demonstrate that the uniformity and quality of BiVO4 firms are greatly dependent on preparation parameters. Adjustments to the drying procedure, designed to slow solvent evaporation, resulted in improved uniformity as observed through UV-Vis spectroscopy and profilometry. Photoelectrochemical testing of select replicates under illumination confirmed photoactivity, with distinct differences between dark and light conditions. Further experimentation with cyclic voltammetry and chronoamperometry will explore the efficiency of these films in greater detail. This work establishes an effective approach for BiVO4 film preparation for future use in WO3-BiVO4-NiO multilayer electrodes for TEMPO oxidations studies and advancing solar-driven oxidation processes.

Asphaltenes are the heaviest component of crude oil and strongly aggregate during the oil refinement process, fouling equipment and increasing oil runoff. Understanding their propensity for aggregation at the molecular level is crucial for developing strategies to mitigate their role in equipment fouling. Using computational chemistry, we analyzed the dimerization energies of 67 previously published asphaltene structures by running CREST calculations on all possible molecular pairs. Our results reveal that diradical:diradical interactions drive strong aggregation, whereas radical-closed shell interactions are comparable in strength to closed-shell:closed-shell interactions. Additionally, we find that archipelago-type structures weaken dimerization as compared to island-type asphaltenes, likely due to self-association of archipelago structures. These findings provide key insights into asphaltene behavior and suggest potential strategies for disrupting aggregation. Future work will explore whether near-infrared light can be used to disaggregate asphaltenes, offering a novel approach to alleviate asphaltene-related challenges in industry.

Macrocycles are promising drug candidates due to their ability to selectively interact with biological targets. However, predicting their solubility and membrane permeability remains challenging. To probe this, a library of 35 triazine macrocycles was synthesized and the hydrophobicity of each macrocycle was measured using octanol:water partition coefficients (logP).

Unexpectedly, a glycine-derived macrocycle with two primary amine groups displayed high hydrophobicity, contrary to prediction based on conventional computational methods for computing logP (AlogP). Computational analysis revealed that the diamine substitution stabilizes a closed conformation, tethering the macrocycle where its polar groups are shielded from solvent interaction, thus increasing hydrophobicity. Additionally, we found that logP values of heterodimer macrocycles closely approximated the average of their corresponding homodimers, suggesting a predictable trend in partitioning behavior.

We demonstrate how small molecular changes can significantly impact physical properties. By combining synthesis, physical measurements, and computational modeling, our work provides insights into macrocycle behavior that could aid in designing membrane-permeable drug candidates.

The goal of this project is to select the variants of an archaea leucyl-tRNA synthetase (MLRS) to incorporate N-𝜀-acetyl lysine (AcLys) into specific positions of proteins in bacterial cells. Acetylation of lysine is one of the most important post-translational modifications of proteins that regulate their functions. One application of this study is using site-directed incorporation of AcLys to introduce novel functions to proteins. Previously, we successfully randomized five positions in the MLRS active site to generate millions of different variants. Genetic screening procedures were performed to select MLRS variants specific for AcLys. Positive selection is performed in the presence of AcLys where bacterial cells containing MLRS that attach any natural amino acids or AcLys onto the tRNA can survive in the presence of chloramphenicol antibiotics. In the negative selection performed in the absence of AcLys, bacterial cells containing MLRS that attach natural amino acids will die in the presence of 5-FU as a toxic substance is produced. Only cells containing MLRS variants that attach AcLys can survive in the presence of 5-FU, because no toxic substance is produced. Two clones made it through multiple rounds of selection and are being tested for successful incorporation of AcLys at the 7th position of the Z-domain protein. Mass spectrometry will be used to detect the presence of AcLys.

Impact of Sensor Design on Hydrogel-Porous Silicon Structures Capable of Detecting Ion Concentrations in Human Sweat

Dylan Walters1, George Weimer1, Leigh T. Canham,2 and Jeffery L Coffer1

1Department of Chemistry and Biochemistry, Texas Christian University, Fort Worth, TX 76129
2Nanoscale Physics, Chemistry and Engineering Research Laboratory, University of Birmingham, Birmingham, B15 2TT UK

Utilizing the supportive structure of hydrogels, the semiconducting character of porous silicon (pSi) membranes, and the biodegradability of both, a unique biosensor for the chemical analysis of health-relevant analytes can ideally be created.
Hydrogels are water-infused, biodegradable polymer networks. Alginate based hydrogels are particularly useful because of environmental abundance, along with their ability to interface well with human skin. The addition of acrylamide segments to the polymer chains adds stability and useful shelf-life to the material. These characteristics also make them an ideal medium for supporting pSi membranes and simultaneously assimilating them into a wide range of tissues.
Porous silicon (pSi), a highly porous form of the elemental semiconductor, is utilized to measure and conduct electrical signals throughout the hydrogel matrix. In diode form, these membranes exhibit measurable current values as a function of voltage, which can be used to detect bioelectrical stimuli such as the concentration of physiologically relevant ionic species (e.g. Na+, K+, and Ca2+).
Recent experiments center on integrating pSi membranes in Acrylamide/alginate co-polymer hydrogels to test how variations in ion concentration affect the flow of current as a function of applied voltage. pSi membranes ~110 m thick and 79% porosity are fabricated from the anodization of low resistivity (100) Si in methanolic HF at an applied bias of 100 mA/cm2 for 30 min. Membrane pieces ~ 2 mm by 2 mm are heated for one hour at 650°C. They are then fashioned into diodes upon the attachment of Cu wire using Ag epoxy and annealed for 15 minutes at 95°C. The backs of the membranes, the connection to the copper wire, and the copper wire itself are sealed using clear nail polish to prevent current flow from the back of the membranes and bubble formation. In each ion sensing experiment, an electrochemical cell is created by placing two pSi membranes parallel each other ~2 mm apart vertically in a fixed electrolyte composition. Current is measured as a function of applied voltage (typically from 0-5 V) for systems with different NaCl concentrations in the nM to mM range. NaCl solutions are injected directly into the hydrogel in between the two pSi membranes 2 µL at a time. At local concentrations of approximately 0.25M, the magnitude of maximum current response increases with increased volume of ion solution added.
This presentation will focus on the porous silicon hydrogel fabrication protocol, as well as results from experiments with varying NaCl concentrations. Future work is being designed to determine the saturation behavior and the ion concentration limits of the pSi membranes in hydrogels.

Fluorescent small molecule environment-sensitive probes change their emission properties (including emission wavelength, intensity or lifetime) in response to the changes of the environment around them, such as changes in temperature, viscosity, and polarity. Thus, these probes have found numerous applications in sensing and imaging, especially in biologically relevant systems. Ratiometic probes is a special group of molecules that has two or more emission wavelengths that exhibit a relative change in response to changes in the media, which provides an internal calibration, increases signal-to-noise ration, and improves the integrity of sensing. However, synthesis of such molecules is usually non-modular in nature, and it often requires multiple steps coupled with numerous purifications. In this presentation, we will highlight our synthetic efforts on the developments of several types of fluorescence ratiometric probes that are based on versatile fluorescence scaffolds, such as BODIPY and squaraine dyes.

Historically, pharmaceutical companies have created small molecule drugs designed to interfere with chemical reactions. An alternative strategy for therapy relies on inhibiting protein-protein interactions, but larger molecules are required. Nature uses large ring-shaped molecules (macrocycles) to accomplish this task. These molecules present challenges to synthesis: forming rings typically is difficult, expensive, time-consuming and inefficient. In addition, the rules required to make macrocyclic drugs are poorly understood when compared to those for small molecules. Here, a strategy for creating macrocycles is described that addresses the challenges of synthesis: they can be prepared quickly and inexpensively. The basis for this chemistry is stepwise substitution of cyanuric chloride, allowing the target to be prepared in three steps. The advantage of using highly electrophilic molecules like cyanuric chloride is that virtually any primary or secondary amine or amino acid could be used to make a macrocycle. Using a variety of amines has shown to affect properties like hydrophobicity and size, which allows for the creation of a large library of molecules to be tested for biological activity, which mirrors how current drug development programs work. The macrocycle is characterized by NMR spectroscopy and screened for other physical (drug-relevant) properties, such as logP and pKa.

FrogCrew is a comprehensive web-based system designed to simplify the management of TCU Athletics sports broadcasting crews. Traditional manual methods of scheduling, tracking availability, and assigning roles are inefficient and prone to errors. This often leads to miscommunication and scheduling conflicts. To solve these challenges, FrogCrew provides a unified platform for administrators. It enables them to manage game schedules, assign roles based on availability and qualifications, and automate notifications efficiently. Key features include customizable crew member profiles. These profiles allow users to update essential information such as availability, roles, and qualifications. The system also offers an automated scheduling tool that simplifies the process of creating game schedules and assigning roles. Additionally, FrogCrew includes a shift exchange feature. This feature allows crew members to request shift swaps, with automated notifications sent to administrators for approval. The system's reporting tools provide financial reports, position-specific insights, and individual performance analyses. These tools help administrators assess crew utilization and manage costs effectively. By automating core functions, FrogCrew reduces manual workload and minimizes errors. It also improves communication between administrators and crew members, ensuring optimal staffing - ultimately enhancing the execution of our TCU sporting events; Go Frogs!

Wearable smart devices, which continuously capture physiological signals such as heart rate, respiratory patterns, and blood oxygen levels, offer significant potential for the early detection of serious health conditions. Timely diagnosis of diseases such as arrhythmia and sleep apnea can greatly enhance patient outcomes by enabling early intervention. However, extensive collection of diverse, real-world wearable sensor data faces challenges due to privacy concerns, data scarcity, and logistical constraints. This research introduces a novel deep learning framework that integrates publicly available wearable sensor data with synthetic physiological signals generated by large language models (LLMs) to create comprehensive and privacy-compliant hybrid datasets.The proposed framework leverages convolutional neural networks (CNNs), optimized for time-series data analysis, alongside advanced machine learning techniques to identify early signs of arrhythmia, sleep apnea, and related health conditions from physiological data. The integration of synthetic data generated by LLMs addresses critical challenges of limited data availability and privacy concerns, enriching the training datasets with diverse scenarios and physiological variations. Preliminary experimental results demonstrate that the hybrid approach, combining publicly accessible wearable sensor data and LLM-generated synthetic signals, significantly enhances the model's accuracy, generalization capability, and resilience to data variability. Models trained on hybrid datasets consistently outperform those relying solely on real-world data, suggesting that synthetic data provides meaningful supplementation to traditional datasets. This study further highlights how synthetic physiological data can enhance the scalability and efficacy of AI-based health monitoring systems, reducing dependency on extensive clinical data collection. By exploring and validating this innovative data synthesis approach, the research contributes significantly to developing more effective, accessible, and proactive healthcare diagnostic tools, ultimately advancing AI-driven solutions in preventive healthcare.

The iPELiNT project develops an AI-powered patent analysis dashboard designed to streamline the patent prosecution process for attorneys and practitioners. This web application leverages modern technologies including Vue.js with Nuxt3 framework for frontend development, NodeJS with Express for backend services, MongoDB for database management, and integrates AI models from OpenAI to analyze patent documents.

The system features a user-friendly dashboard that allows practitioners to upload patent applications, analyze document health, view CPC prediction analytics, examine keyword relevance, and identify potential prior art conflicts. Key functionality includes document parsing, automated health checks, Art Unit prediction, and generation of actionable reports. The solution also incorporates user account management, notification systems, and specialized document generation tools.

Development followed an iterative process with clearly defined milestones and tasks distributed across team members. The project addresses a critical need in the patent industry by providing an all-in-one platform that simplifies complex patent analysis, replacing traditionally fragmented and cumbersome tools with a streamlined, intuitive interface.

The completed iPELiNT dashboard enhances efficiency for patent professionals, improving application quality through AI-powered insights, and ultimately streamlining the patent prosecution workflow with modern design principles and cutting-edge technology.

Designed to empower students with transparent, real-time insights, this innovative digital platform provides comprehensive reviews of classes and instructors, enabling informed academic decision-making. It aggregates detailed evaluations of course content, teaching effectiveness, workload, and overall classroom experience, offering a dynamic alternative to traditional end-of-semester surveys that frequently deliver delayed or insufficient feedback. Backed by survey research underscoring the vital role of timely, honest assessments in shaping successful academic journeys, the platform bridges the gap between institutional data and the practical needs of students. Its intuitive, user-friendly interface allows seamless navigation through a wealth of peer-generated feedback, making it easier for students to select courses that align with their educational goals and personal learning styles. Moreover, by establishing a constructive feedback loop, it provides educators with actionable insights to refine their teaching methods and foster continuous improvement. This collaborative environment not only enhances individual learning experiences but also contributes to building a more effective, accountable educational community. Through open dialogue and shared knowledge, the platform drives positive change, promoting excellence and ensuring that every academic decision is supported by reliable, student-centered information. By continuously evolving based on extensive user feedback, the platform remains dedicated to advancing educational quality and student success.

Public property tax data is often presented in raw formats, making it difficult for the average user to interpret. Our client initially developed a product that provided access to Kern County property tax information only. Our project enhances accessibility by developing ParcelSearch.com, a platform that centralizes property tax data. With this rebranded system, we have expanded coverage to include Kern, Monterey, San Luis Obispo, and Tulare Counties, with plans for further expansion. Users can create accounts and choose from various subscription plans to conduct property searches using multiple search criteria: owner name, parcel number, and legal descriptions. With the development of a user-friendly interface and expanded search functionalities, the platform caters to realtors, investors, and homeowners seeking property insights. This system was built using modern web technologies, including Vue.js for the frontend, Java and Spring Boot for the backend, and PostgreSQL for database management, to name a few. Future plans include expanding nationwide to create an all-encompassing and user-friendly property data platform.

Academic advising presents significant challenges in both time management and complexity. Currently, students navigate between two advising options: generic online resources and personalized consultations with professors and advisors. While personalized advisement offers tailored advice, professors cannot be expected to meet with every undergraduate in their major, especially as enrollment grows, and academic advisors may lack specialized knowledge required for some majors. Echelon addresses this gap by creating a middle ground between generic and personalized advising, offering students an effective supplement and saving time for all parties involved. Echelon functions as an intelligent chatbot assistant powered by large language models such as Llama 3 and Mistral. Upon signup, students share their academic records, enabling Echelon to create individualized profiles that consider key factors such as major/minor selection and performance in critical courses. The project is being built using TypeScript and Rust with Svelte and Axum frameworks, respectively. Echelon utilizes PostgreSQL for user account and conversation storage and Qdrant for vector storage and retrieval. Designed with flexibility in mind, Echelon can be deployed at any university, given basic institutional information such as course catalogs and degree requirements.