Materials databases lie at the heart of future data-driven discovery in energy-related fields, say researchers from Tohoku ...

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.

The hope for quantum computers is that the devices will be able to solve complex tasks such as predicting how chemicals react or cracking encrypted text. One of the main reasons that the machines are ...

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.

At Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences, Yongtao Liu is building AI-driven “closed-loop” ...

From creating lightweight yet durable prosthetics to designing new types of solar panels and batteries, materials engineers combine their expertise in physics, chemistry, biology, and engineering to ...

An introductory course focused on the new and existing materials that are crucial for mitigating worldwide anthropogenic CO2 emissions and associated greenhouse gases. Emphasis will be placed on how ...