Sixteen new START.nano companies are developing hard-tech solutions with the support of MIT.nano
Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.
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Materials science and engineering
MIT researchers use AI to uncover atomic defects in materials
A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.
Read MoreMIT engineers design proteins by their motion, not just their shape
An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.
Read More3 Questions: On the future of AI and the mathematical and physical sciences
Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.
Read MoreAccelerating science with AI and simulations
Associate Professor Rafael Gómez-Bombarelli has spent his career applying AI to improve scientific discovery. Now he believes we are at an inflection point.
Read MoreHow 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.
Read MoreNew materials could boost the energy efficiency of microelectronics
By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.
Read MoreChecking the quality of materials just got easier with a new AI tool
Acting as a “virtual spectrometer,” SpectroGen generates spectroscopic data in any modality, such as X-ray or infrared, to quickly assess a material’s quality.
Read MorePrintable aluminum alloy sets strength records, may enable lighter aircraft parts
Incorporating machine learning, MIT engineers developed a way to 3D print alloys that are much stronger than conventionally manufactured versions.
Read MoreAI system learns from many types of scientific information and runs experiments to discover new materials
The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.
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