AI helps design new materials that work in the real world
The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that’s essential to fertilizer and other products.
Read MoreBy focusing on electrolytes, MIT scientists are making sodium-metal batteries a more practical energy storage option.
Read MoreInitial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.
Read MoreDean 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.
Read MoreA new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.
Read MoreNuclear 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.
Read MorePhD student Miranda Schwacke explores how computing inspired by the human brain can fuel energy-efficient artificial intelligence.
Read MoreThe new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.
Read MoreWith SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
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