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.
Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.
Read MoreMIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
Read MoreAI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
Read MoreSystem developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
Read MoreSolubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
Read MoreThe Initiative for New Manufacturing is convening experts across the Institute to drive a transformation of production across the U.S. and the world.
Read MoreThe MIT Energy Initiative’s annual research symposium explores artificial intelligence as both a problem and a solution for the clean energy transition.
Read MoreChemists could use this quick computational method to design more efficient reactions that yield useful compounds, from fuels to pharmaceuticals.
Read MoreStuart Levine ’97, director of MIT’s BioMicro Center, keeps departmental researchers at the forefront of systems biology.
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