Research

Assistant Professor Dean Price sees a bright future for nuclear power, and he believes artificial intelligence can help us realize that vision

Assistant Professor Sophia Henneberg is developing stellarators to harness fusion energy

MIT's Bilge Yildiz and Ju Li found a way to predict how efficiently materials can transport protons in clean energy devices and other advanced technologies.

“Use of AI for materials development is booming right now,” says Ju Li, MIT’s Carl Richard Soderberg Professor of Power Engineering. He notes two main directions. First, AI makes possible faster physics-based simulations at the atomic scale. Second, AI can help guide experiments in real time as they take place in the lab.

Taylor Hampson, masters student in MIT’s Department of Nuclear Science and Engineering is modeling the behavior of an unconventional rocket engine that will heat propellant using nuclear energy.

Recognizing that nuclear waste continues to be a bottleneck in the widespread use of nuclear energy, NSE doctoral student, Dauren Sarsenbayev, is developing models that explore how to address the problem.

A new study by Haruko Wainwright and collaborators analyzes different nuclear waste management strategies, with a focus on the radionuclide iodine-129.

Sophia Henneberg focuses on developing, utilizing, and extending optimization tools to identify new, promising stellarator designs, which are a promising path toward fusion energy. Ethan Peterson focuses on improving radiation transport and transmutation methods for the design of fusion technologies, as well as whole-facility modeling for fusion power plants. Dean Price focuses on the simulation and control of advanced reactors, with expertise in uncertainty quantification, scientific machine learning, and artificial intelligence for nuclear applications.

PhD student Miranda Schwacke works with Prof Bilge Yildiz to explore how computing inspired by the human brain can fuel energy-efficient artificial intelligence.

In a new study, Mingda Li and MIT researchers evaluated quantum materials’ potential for scalable commercial success — and identified promising candidates.