Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...

In late 2023, a robotic laboratory at Lawrence Berkeley National Laboratory ran nonstop for 17 days without a single human ...

For more than half a century, materials scientists have struggled with how to simulate the complexity of polymer materials.

How can artificial intelligence (AI) machine learning models be used to identify new materials? This is what a recent study published in Nature hopes to address as a team of researchers investigated ...

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...

Using the second-nearest neighboring atoms to predict metallic glass stability can help researchers more accurately model the ...

A recent study published in Small highlights how machine learning (ML) is reshaping the search for sustainable energy materials. Researchers introduced OptiMate, a graph attention network designed to ...

Join us to learn about how to use cutting edge GPU infrastructure to solve real world material discovery problems with AI and unsupervised machine learning. Our lab in the Department of Materials ...

The exploration of Haeckelites gained momentum following the experimental synthesis of beryllium oxide (BeO) in this configuration. This achievement sparked interest in the potential of other elements ...

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...