Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional ...

In a collaboration between Murata Manufacturing Co., Ltd., and the National Institute for Materials Science (NIMS), researchers have built a comprehensive new database of dielectric material ...

Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However, the lack of a ...

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 ...

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...

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 ...

If large-scale datasets of experimental data can be built through this approach, it is expected to enable researchers to gain ...