Arunkumar Seshadri
Research Scientist
arunmdm@mit.edu
617-452-3384
NW12-209
Dr. Seshadri is currently a Research Scientist in the Department of Nuclear Science and Engineering at MIT. He earned both his Ph.D. and Master's degrees in Nuclear Science and Engineering from MIT, specializing in Nuclear Materials, Radiation Interactions, and Thermal Hydraulics. Additionally, he holds a joint appointment at the Idaho National Laboratory.
His primary focus is on experimental research within two research groups at MIT: the Nuclear Innovations Fission Technology group and the Center for Reactor Instrumentation and Sensor Physics. He also collaborates closely with the MIT Nuclear Reactor Lab, where he leads efforts in post-irradiation examination. Prior to his role at MIT, he served as a postdoctoral research associate at the Idaho National Laboratory.
Comprehensive experimental studies at both micro and engineering scales are conducted to characterize corrosion, mechanical properties, thermophysical behavior, and thermal hydraulics of accident tolerant fuels (ATFs). In-reactor testing at MITR and CALPHAD simulations are utilized to enhance the technological readiness of ATF coatings and advanced silicon carbide composites. The development of advanced hydride moderators and high-entropy metallic and ceramic alloys are also explored, with a focus on performance in coupled radiation and high-temperature environments for next-generation reactors and space nuclear propulsion systems.
The effects of ionizing radiation, high temperatures, and complex corrosive environments on the surface chemistry of various metals and alloys are investigated. Multiscale characterizations are conducted using high-resolution techniques such as TEM, SEM, XPS, EDS, and WDS to unravel intricate micro- and nanoscale interactions.
Novel techniques utilizing Co-60 and gamma irradiation are developed to create scalable micro- and nanoengineered materials. These materials exhibit enhanced heat transfer, corrosion resistance, and fouling resistance, contributing to sustainable energy applications.
Experimental diagnostic capabilities for two-phase flow phenomena are advanced through capacitance, optical, and acoustic imaging. Tailored experiments are performed to develop phenomenological models that account for morphological changes and surface chemistry relevant to quenching and reflooding processes in commercial light water reactors (LWRs).
Physics-informed machine learning and advanced neural network architectures are employed to innovate instrumentation for complex experimental testing and enhance operational efficiency in nuclear power plants.