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 ...
For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...
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 ...
Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon steel but the ...
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 ...
Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in fusion reactors, but the ultra-high heat can damage its microscopic ...
Two-dimensional (2D) quantum materials offer unique electrical and optical properties for future electronic and sensing technologies. Tungsten ditelluride (WTe2) is especially promising due to its ...
Researchers have used machine learning to design nano-architected materials that have the strength of carbon steel but the lightness of Styrofoam. The team describes how they made nanomaterials with ...
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