During the second semester of my freshman year at Old Dominion University, I applied to and was accepted as a student researcher on the EPA P3 Student Design Project involving the ecological extraction of lithium from geothermal brine using a novel ion sieve method. The project aimed to form an interdisciplinary team—at the time of joining, I was a dual Computer Engineering and Cyber Operations major working within the civil and environmental engineering department. Our initial team and the awarded grant were highlighted in an article released by ODU: ODU Team Researches Ecologically Friendly Methods of Extracting Lithium. The journal paper resulting from this effort “Lithium Recovery from Aqueous Solution Using Zirconium-Enhanced Ion Sieve” was accepted to Elsevier Advanced Power Technology.

Lab Work

The lab work for this research took place at the Biomass Lab at Old Dominion University. I began assisting with experiments three days a week in the late afternoon following work at my internship at NIWC. I gained practical experience in:

• Precise measurements using analytical balances
• Forming chemical mixtures
• Accurately pouring and transferring liquids
• Measuring pH
• Chemical safety protocols
• Cleaning and maintaining test equipment
• ICP analysis

Overall, I gained a deep appreciation for the time and difficulty of the scientific process in a physical lab setting. This was particularly impactful for me, as my major and interests primarily involve computer and software-related topics—research environments that operate fundamentally differently than working in a physical lab. When I work on a program or algorithm, the development environment is always accessible and results are instantaneous. This lab experience gave me a true appreciation for the time-intensive, physical nature of experimental scientific work. An experiment needing to be rethought or reworked in this environment isn’t as simple as retyping and rerunning a program—it involves returning to the lab, using real physical materials with associated costs, reinvesting countless hours, and for timed experiments, maintaining significant commitment to return at specific intervals. During some experiments, I observed our lead graduate researcher restructuring their entire daily schedule around experimental timelines.

During my time conducting this lab work, I had elected to narrow the focus of my Computer Engineering degree to specialize in Modeling and Simulation Engineering. The real-world impacts of failed experiments and the limitations on testing throughput due to physical resource constraints became clearly highlighted as problems that modeling and simulation is designed to address. This expanded my previous view of modeling and simulation from my background as a US Navy Intelligence Analyst to include applications in scientific discovery, such as developing ion sieves for lithium extraction like in this project.

Market Analysis

Outside of lab work, one of my largest contributions involved conducting market analysis comparing this powder extraction technology to other methods available in industry. I also investigated geothermal power companies to identify which showed the most inclination to pursue mineral extraction technologies like the one we were researching. This work required extensive effort in finding sources and extracting key data points, including determining what would constitute key indicators of a company’s inclination to engage with developmental technologies. I created visualizations and comparative analyses referencing company websites, research papers, press releases, and industry reports. This line of analysis also involved examining known geographic information concerning mineral concentration levels in different regions with geothermal power plants to determine where our specific ion sieve could offer advantages and how this differed from currently deployed methods. Two of the slides I created for a presentation of these findings are presented below.

Research Poster Design

As part of the EPA P3–funded lithium extraction research project at Old Dominion University, I was responsible for designing and creating the research poster presented at ODU’s inaugural Research and Creativity Expo. The goal of the poster was to clearly communicate the core ideas, methods, and findings of the project in an environment where viewers are quickly scanning and engaging at different levels of depth. I focused on reducing text, emphasizing visual structure, and using process diagrams and annotated data visualizations to convey the experimental workflow and key results efficiently. This work allowed me to combine my involvement in the research itself with an interest in design and technical communication, and helped shape my approach to presenting complex scientific information in a clear, accessible way. I have documented more about my design decisions and process creating the poster in the blog post Designing a Research Poster for the ODU Research and Creativity Expo.

Conclusion

This project marked my first involvement in university research and proved formative in several ways. Working outside of a computer engineering and instead in environmental chemistry taught me the value of interdisciplinary collaboration and exposed me to research methodologies beyond my primary field. The contrast between computational and physical experimentation deepened my understanding of how modeling and simulation can accelerate scientific discovery by reducing the cost and time barriers inherent in physical experimentation.

Key takeaways:

Interdisciplinary perspective: Working outside my primary discipline expanded my technical knowledge and gave me insight into how different fields approach problem-solving. This experience reinforced my interest in applying computational methods to physical science problems.

Practical research skills: Beyond technical lab skills, I developed capabilities in literature review, market analysis, data visualization, and scientific communication—all critical for conducting and presenting research effectively.

Understanding modeling and simulation’s role: Witnessing firsthand the resource constraints and time investments required for physical experimentation clarified the strategic value of computational modeling.