News

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’s Mingda Li and a team of researchers from MIT, Harvard, Princeton and ANL have shown that Using machine learning and simple X-ray spectra, can uncover compounds that might enable next-generation computer chips or quantum devices.

Spotlight: In a residency supported by the Department of Energy, the NSE PhD candidate, Evan Leppink, will explore the high-field side of the DIII-D tokamak.

Co-led by NSE’s Bilge Yildez and DMSE’s Yet-Ming Chiang, The Center for Electrification and Decarbonization of Industry, unites MIT climate researchers to create scalable clean energy solutions under one roof. NSE’s Ju Li is one of sixteen collaborators who form the MIT team.

The 48th Annual Dr. Martin Luther King Jr. Celebration, held virtually on February 10 themed ‘Open your mind and heart to truth and love’

Professor Mingda Li received a 2021 Early Career Research Award given by the DoE Basic Energy Sciences Program. Given annually, the award is designed to bolster the research in science by providing support to exceptional researchers during the crucial early career years. It will support Li's research program — Machine Learning Augmented Multimodal Neutron Scattering for Emergent Topological Materials. Massachusetts Institute of Technology 77 Massachusetts Avenue, 24-107 (map) Cambridge, MA 02139 nse-info@mit.edu

Center for Electrification and Decarbonization of Industry, led by Yet-Ming Chiang and Bilge Yildiz and Decarbonizing and strengthening the global energy infrastructure using nuclear batteries, led by Jacopo Buongiorno are finalists in the Climate Grand Challenges competition launched in July 2020.

Spotlight: Associate Professor Areg Danagoulian credits mentorship with helping him establish a path through nuclear physics.

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

One of six from MIT elected this year, Prof Nuno Loureiro is recognized for “transformative contributions to the theory of magnetic reconnection and for elucidating the fundamental role of hierarchical reconnection phenomena in plasma turbulence, with broad applications in laboratory, space, and astrophysical systems.”