Computer Modeling

Wickert, a third-year undergraduate is double majoring in nuclear science and engineering and physics. Together the disciplines allow her to develop a detailed theoretical knowledge base she can apply to work in nuclear energy.

The winners of the first-ever Climate Grand Challenges will become multiyear flagship research projects, helping define a new research agenda focused on addressing complex unsolved climate problems and bringing high-impact solutions to the world on an accelerated basis.

NSE graduate student Abhilash Mathews is testing a simplified turbulence theory’s ability to model complex plasma phenomena using a novel machine-learning technique.

By incorporating the scattering of RF waves into fusion simulations, MIT physicists improve heating and current drive predictions for fusion plasmas.

Xu, a PhD student in NSE, is seeking new, more efficient materials to be utilized for the construction of computer components.

In a September 2020 essay in Nature Energy, three scientists posed several “grand challenges” — one of which was to find suitable materials for thermal energy storage devices that could be used in concert with solar energy systems. Fortuitously, Mingda Li —...

Koroush Shirvan, Ben Forget and other MIT researchers show that deep reinforcement learning can be used to design more efficient nuclear reactors.

The reusable mask would include a heated copper mesh that’s powered by a battery and surrounded by insulating neoprene.

MIT team has made strides toward a system, which uses physical, analog devices that can much more efficiently mimic the brain’s learning process, for neural network AI systems.