Abstract
My technical project focuses on measuring thermal conductivity of different materials at temperatures of 10K-300K using the 3-omega method. Knowing how materials behave at different temperatures is useful for the quantum computing industry to design more efficient computers. Although my technical and STS projects address different aspects of computing technology, they are connected by a shared focus on how emerging technologies are developed and implemented. As technological capabilities and computational demands continue to grow, the demand for AI data centers also continues to increase. As a result, many citizens find themselves lacking a voice, as the local government and corporations make infrastructure decisions that lack transparency and prioritize financial gain. Through the use of stakeholder theory and a case study on the data center construction in Warrenton, VA, my STS paper focuses on analyzing the role of citizens in infrastructure decisions in Virginia, and how they navigated through informational asymmetry and ultimately halted the construction of the data center.
The technical portion of my thesis focused on developing a lower-cost thermal conductivity testing system as an alternative to conventional systems that rely on liquid helium. Since liquid helium is expensive, my team designed a system that uses helium gas in an effort to reduce operating costs while still supporting thermal conductivity measurements. My team focused on designing, analyzing, and manufacturing a structural support to hold the cryostat upright, a sample mount for the test material, and a plate designed to withstand a vacuum of 10-8 torr. In the second phase of the project, we worked to establish the vacuum and electrical connections needed to perform the 3-omega method for thermal conductivity testing. Although a broken compressor prevented us from reaching cryogenic temperatures, we successfully achieved a vacuum of 10-4 torr and conducted thermal conductivity testing from room temperature and above. These results are significant because they demonstrate partial validation of a more affordable testing system that could make thermal conductivity measurements more accessible for future research and engineering applications.
In my STS research, I analyzed the proposed Amazon data center in Warrenton, Virginia, using stakeholder theory to examine how local citizens responded to infrastructure decisions made by corporations and government officials. My paper focuses on the different motives and values of the involved stakeholders, including residents, government officials, and corporations. Additionally, I examined how residents navigated informational asymmetry, challenged a lack of transparency, and exercised stakeholder power in opposition to the project. This work is significant because it demonstrates that infrastructure decisions are not only based on technical or economic factors, but also require public input and ethical considerations. Lastly, it demonstrates that stakeholder positions are dynamic rather than fixed.
When designs consider technical, organizational, and cultural elements simultaneously, engineers are able to create solutions that are not only safe and functional, but also equitable and socially accepted. An STS perspective demonstrates that engineering problems are not only technical because they exist in a larger system that can be shaped by institutions and cultural values. As an engineer, it can be easy to prioritize the technical requirements, especially when working on a small part of a large system. STS perspectives broaden that scope by encouraging engineers to consider how decisions affect different stakeholders and how organizational priorities can shape engineering choices. This supports ethical responsibility by helping engineers recognize that good design is not only about performance, but also encompasses values like fairness and accountability.
Notes
School of Engineering and Applied Science
Bachelor of Science in Mechanical Engineering
Technical Advisor: Ethan Scott
STS Advisor: William Davis
Technical Team Members: Mia Petersen, Mary Cotter, Mohammad Ahmadzai, Andrea Rojas Ramirez, Brandon Flores Castaneda, Matthew Alexander Orellana-Aquino, Raymond Ni, Philip Li, Jonathan Martinez, Tristan Huynh, Jimmy Bastos Infantas, Hannah Heafner
