Nanoscale transistors could enable more efficient electronics
Researchers are leveraging quantum mechanical properties to overcome the limits of silicon semiconductor technology.
Materials science and engineering
AI model can reveal the structures of crystalline materials
By analyzing X-ray crystallography data, the model could help researchers develop new materials for many applications, including batteries and magnets.
Read MoreProton-conducting materials could enable new green energy technologies
Analysis and materials identified by MIT engineers could lead to more energy-efficient fuel cells, electrolyzers, batteries, or computing devices.
Read MoreMachine learning unlocks secrets to advanced alloys
An MIT team uses computer models to measure atomic patterns in metals, essential for designing custom materials for use in aerospace, biomedicine, electronics, and more.
Read MoreAI method radically speeds predictions of materials’ thermal properties
The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.
Read MoreNew computer vision method helps speed up screening of electronic materials
The technique characterizes a material’s electronic properties 85 times faster than conventional methods.
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