Modeling and Simulation

Amelia Trainer applied to MIT because she lost a bet. As part of what the fourth year NSE doctoral student labels her “teenage rebellious phase,” Trainer was quite convinced she would just be wasting the application fee were she to submit an...

It is a problem that has beguiled scientists for a century. But, buoyed by a $625,000 Distinguished Early Career Award from the U.S. Department of Energy (DoE), Matteo Bucci, an associate professor in the Department of Nuclear Science and Engineering (NSE), hopes...

Engineers working on “analog deep learning” have found a way to propel protons through solids at unprecedented speeds.

By studying the dynamics of plasma turbulence, MIT researchers are solving one of the mysteries of the origins of cosmological magnetic fields.

Clean electricity and stored heat from nuclear power and intermittent electricity from wind and solar can be efficiently converted to green hydrogen, fuels and chemicals using protonic ceramic electrolyzers with exceptional performance and stability. The reduction in the use of fossil fuels...

In the forward to his memoir in progress, Sidney Yip describes his life, and 50-plus-year career as a professor of nuclear science and engineering (NSE), as touched by “luck and contentment.” But while the 86-year-old emeritus professor finally has some time to...

Friday, April 1, 2022. 1:00 PM – 3:20 PM ET Koch Institute, 500 Main Street first floor Main Corridor and Galleries and Auditorium 76-156 The MIT Department of Nuclear Science and Engineering held its annual Research Expo on April 1, 2022. The...

MIT researchers discovered hidden magnetic properties in multi-layered electronic material by analysing polarized neutrons using neural networks. Superconductors have long been considered the principal approach for realizing electronics without resistivity. In the past decade, a new family of quantum materials, “topological materials,”...

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

NSE PhD candidate Lucio Milanese expands a theory of turbulence to include both ionized and non-ionized fluids.