This study aims to use chemodynamics to engage the interplay between societal actions and environmental response. The project will build upon data from thermogravimetric and isotopic analysis capturing macroscopic soil chemodynamics in response to suburbanization in the Dallas-Fort Worth Metroplex (DFW). The DFW is one of the fastest growing metro areas in the US. Our early data suggests that a minimum of 30-yrs is the required period of lawn care before key chemodynamic indicators of soil health/resilience, such as R50 and isotope 13C (quantity and quality, is needed for lawns to return to their pre-suburbanization environmental status.

The objective is to examine implications at the microphysical and molecular-level via: Assessing how differences in the molecular composition of soil organic matter from a suburban lawn changes over time.

We propose a GIS project analyzing waste disposal accessibility by comparing recycling quality between low-income and high-income neighborhoods. Using spatial analysis and field data, we will compare the amount of waste generated to the income of Los Angeles counties, and document any trends. The findings will provide insights into potential disparities in waste management services and inform policy recommendations for improving recycling programs in underserved communities.

The purpose of this project is to determine if California's raging wildfires are having a detrimental effect on the state’s tree populations/health. Two main components of this project would be, a model of California's tree density/canopy cover in 1990, and a model of California’s tree density/canopy cover in 2020. The goal of this project is to determine if an increase in wildfires is a key factor in the decrease of California tree density, and if so, make recommendations for further research on how to protect trees from this natural disaster.

The Coll de Montllobar cliffs in the Pyrenees Mountains contain plant fossils known as root models, which show signs of oxidation and reduction along a depositional dip, indicating varying environmental conditions Since plant roots do not grow below standing water levels, these fossilized roots and their distribution can serve as markers for past water table positions. This study examines whether root density decreases toward the bottom of the channels, indicating that roots stopped growing once they reached below the water table. If the roots disappear at a certain depth, it suggests that the bar was saturated at that level, stopping root growth. By analyzing the presence and absence of these roots, we aim to determine if they mark a clear boundary indicating historical water table levels. Our findings contribute to understanding past depositional environments and hydrological conditions in this region

The Barnett Shale formation in the Fort Worth Basin has been a substantial producer of oil and gas energy resources. The Barnett Shale serves as an ideal testing ground for innovative approaches to subsurface analysis, offering both abundant production history and a wealth of existing data. This study integrates innovative thermal analysis techniques with AI-driven workflows to rapidly process and interpret large volumes of geochemical data. We aim to identify and evaluate geochemical variability and the distribution, content, and quality of geogenic carbon with depth across key stratigraphic intervals. Expanding subsurface applications of AI and machine learning enhances the scalability of resource assessments and underscores the broader potential of these emerging analytical tools in energy exploration.

Pesticide degradation in the environment is an important element when it comes to understanding long-term soil and water contamination. There are many key molecular factors like molecular weight and octanol-water partitioning (logP) that influence how pesticide degradation works. By taking a computational approach, we derived daughter molecules of ferulic acid, 1,2,4-Trihydroxybenzene, and vanillic acid which share similarities with pesticide byproducts. We specifically computed molecular weight and logP for each derivative to assess their potential to contaminate the environment. By comparing these values to oxidative pesticide breakdown products from glyphosate (Roundup), atrazine, and chlorpyrifos, we identified solubility trends that may influence the transport of these molecules into soils and water systems. These findings provide insight into the environmental risks associated with pesticide use and degradation, potentially aiding in the design of more sustainable agricultural chemicals.

The "You Belong in Chemistry" Periodic Table is a unique and innovative visual representation designed to foster unity and a sense of belonging among students within the TCU College of Science and Engineering. This table uses the traditional periodic table, replacing chemical elements with students, each symbolizing a distinct individual who contributes to the diverse academic environment. The table is not just an artistic display but a tool for connecting students, encouraging collaboration, and highlighting the central role of the Chemistry Club: creating a supportive and inclusive space. Through this representation, students are reminded that, regardless of their backgrounds or academic focus, they have a home within the chemistry community, where they can grow, learn, and thrive together. By bridging gaps and strengthening bonds, the Student Periodic Table stands as a symbol of inclusivity and community.

Artificial intelligence’s integration into healthcare promises more effective and higher-quality patient care. However, its impact on the human aspects of care, such as trust and bias, remains not fully understood. Through a literature review and analysis, this poster provides an up-to-date overview of how the implementation of AI affects patient-provider interactions. This research seeks to answer the question: “How does AI-driven diagnosis and treatment influence patient-provider interactions, and what role does AI bias play in shaping trust and healthcare disparities?” Our findings show a consensus that AI improves productivity, but there is concern that the public’s growing trust in AI over human providers may reshape relationships and perpetuate healthcare disparities. Understanding these dynamics is crucial for developing AI systems that enhance care while maintaining equity and trust in healthcare settings.

At the heart of the Texas Christian University chemistry department, there are two main factors contributing to chemical education: professors and students. Our students are vitally important to the chemistry department as they not only receive education but are educators themselves. TCU chemistry club members serve as sources of experience, knowledge, and study skills, including those outside the context of chemistry. The challenge of chemical education is the “translation” of material to a diverse student body. What is special about these “student educators” however, is their ability to do so to individuals of all ages and all skill levels. The TCU chemistry department has many different teaching opportunities in both general and organic chemistry labs and lectures such as Teaching Assistants (TAs) and peer tutors. Of these positions, many are filled by the TCU chemistry club student body. Our Chemistry Club students go beyond the education of fellow undergraduates, as they educate students in the local elementary schools about science. Our Chemistry Club members have become well-rounded and effective educators through the variety of services provided to them such as, peer guides, university classes, and supportive professors. The Chemistry Club students provide knowledge of chemistry but they also encourage confidence, and serve as a source of mentorship in the Fort Worth community. At TCU we strive to not only learn but also share the wealth of wisdom gained during our time in the chemistry department at TCU.

Historically, students have envisioned scientists as white males in lab coats, reinforcing exclusionary stereotypes that can discourage diverse participation in STEM. Mentorship has the potential to broaden perspectives, enhance self-esteem, and support identity development, yet research on its specific impact in middle school remains limited. This study examines how a structured mentorship program influences middle school students’ perceptions of scientists and their own scientific identity, particularly in STEM and healthcare professions, asking: How does mentees’ identity in science and healthcare professions develop through interactions with mentors and peers? This qualitative study follows seven 7th- and 8th-grade students (ages 13–14) in a year-long mentorship program led by junior college undergraduates. The research employs a pre- and post-intervention assessment using the Draw-a-Scientist Test (DAST) alongside open discussions and interviews to evaluate shifts in students’ identity perceptions. DAST drawings are analyzed with a rubric evaluating gender, activity, location, and skin tone to identify shifts toward more inclusive representations. The study anticipates that students will depict more diverse scientists over time, moving beyond traditional stereotypes. Findings are expected to reveal more diverse depictions of scientists, offering insights into how mentorship fosters inclusivity and belonging in STEM for underrepresented middle schoolers.