Nuclear science and engineering
Nuclear science and engineering

Nuclear science and engineering

Artificial Intelligence Batteries Computer modeling DMSE Electric vehicles Energy storage Lithium-ion Materials science and engineering MIT.nano National Science Foundation (NSF) Nuclear science and engineering Renewable energy Research School of Engineering Transportation

Solving the solvent problem

By focusing on electrolytes, MIT scientists are making sodium-metal batteries a more practical energy storage option.

Artificial Intelligence Automation Awards, honors and fellowships Computer modeling Department of Energy (DoE) Energy Graduate, postdoctoral Human-computer interaction Mechanical engineering Nuclear power and reactors Nuclear science and engineering Profile Renewable energy Research ROTC School of Engineering Software Students U.S. Armed Forces

Working to automate nuclear plant operations

PhD student Lauren Fortier is building on the experience she gained operating a nuclear plant for the Navy to solve a critical hurdle in the wider adoption of the energy source.

Administration Artificial Intelligence Center for Computational Science and Engineering Chemical engineering Department of Energy (DoE) EAPS Faculty Funding Industry Laboratory for Nuclear Science Manufacturing Mathematics Mechanical engineering Nuclear science and engineering Physics Plasma Science and Fusion Center Quantum Computing Research Laboratory of Electronics School of Engineering School of Science

MIT projects selected for funding under US Department of Energy’s Genesis Mission

Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.

Artificial Intelligence Computer science and technology Energy Energy efficiency Energy storage Innovation and Entrepreneurship (I&E) Nuclear science and engineering School of Engineering Startups Sustainability Sustainable computing Technology and society Water

Startup’s nuclear-inspired cooling system could make data centers more sustainable

Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI.

Artificial Intelligence Computer modeling Energy Faculty machine learning Nuclear power and reactors Nuclear science and engineering Profile Renewable energy School of Engineering Sustainability

Working to advance the nuclear renaissance

Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.

Artificial Intelligence Batteries Computer modeling Department of Energy (DoE) DMSE Electrical engineering and computer science (EECS) machine learning Manufacturing Materials science and engineering Nanoscience and nanotechnology National Science Foundation (NSF) Nuclear science and engineering Research School of Engineering Semiconductors Solar

MIT researchers use AI to uncover atomic defects in materials

A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

Algorithms Artificial Intelligence Civil and environmental engineering Computer modeling Department of Energy (DoE) Energy Graduate, postdoctoral Nuclear power and reactors Nuclear science and engineering Nuclear security and policy Profile School of Engineering Students

Working to eliminate barriers to adopting nuclear energy

Nuclear waste continues to be a bottleneck in the widespread use of nuclear energy, so doctoral student Dauren Sarsenbayev is developing models to address the problem.

Artificial Intelligence Community Computer science and technology DMSE Energy Energy efficiency Graduate, postdoctoral Nuclear science and engineering Profile Research School of Engineering Science communications Students Sustainability

The brain power behind sustainable AI

PhD student Miranda Schwacke explores how computing inspired by the human brain can fuel energy-efficient artificial intelligence.

Artificial Intelligence DMSE Energy machine learning Materials science and engineering MIT.nano Nanoscience and nanotechnology Nuclear science and engineering Research School of Engineering

AI system learns from many types of scientific information and runs experiments to discover new materials

The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.

Artificial Intelligence Department of Energy (DoE) Energy machine learning Materials science and engineering National Science Foundation (NSF) Nuclear science and engineering Quantum mechanics Research School of Engineering Superconductivity

New tool makes generative AI models more likely to create breakthrough materials

With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.