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.
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Semiconductors
Q&A: Rethinking how innovation happens
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
Read MoreQ&A: Rethinking how innovation happens
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
Read MoreSixteen 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.
Read MoreMIT 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 MoreAgreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.
Read MoreIntroducing the MIT Generative AI Impact Consortium
The consortium will bring researchers and industry together to focus on impact.
Read MoreNew computational chemistry techniques accelerate the prediction of molecules and materials
With their recently-developed neural network architecture, MIT researchers can wring more information out of electronic structure calculations.
Read MoreMIT engineers grow “high-rise” 3D chips
An electronic stacking technique could exponentially increase the number of transistors on chips, enabling more efficient AI hardware.
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