research laboratory to study “bad bubbles” that cause defects in metal alloys used to produce engine turbine blades and semiconductor crystals that are crucial components in electronic devices.

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

A particle accelerator that produces intense X-rays could be squeezed into a device that fits on a table, my colleagues and I have found in a new research project. The way that intense X-rays are ...

When you need tools or parts for something you’re working on around the house, you head to the nearest hardware store. Space travelers don’t have that luxury and may have to make their own tools and ...

Liam Fedus, OpenAI’s VP of research for post-training, is leaving the company to found a materials science AI startup. The Information initially reported Fedus’ plans. In a statement on X, Fedus ...

Key TakeawaysThe Materials Project is the most-cited resource for materials data and analysis tools in materials science.The ...