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.

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.

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

The University of Iowa has been awarded $1.5 million to advance materials science research by leveraging various materials’ ...

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.

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 ...

We are entering a new era in science — the fourth paradigm, according to Kristin Persson, a professor in materials science at the University of California in Berkeley, United States. The first ...