How generative AI can help scientists synthesize complex materials
MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
Chemical engineering
How artificial intelligence can help achieve a clean energy future
AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
Read MoreA new generative AI approach to predicting chemical reactions
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
Read MoreA new model predicts how molecules will dissolve in different solvents
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
Read MoreMIT gears up to transform manufacturing
The 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.
Read More3 Questions: Visualizing research in the age of AI
Felice Frankel discusses the implications of generative AI when communicating science visually.
Read MoreThe multifaceted challenge of powering AI
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
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