Engineers at NIMS Develop a System That Captures All the Elements of Trial and Error in Material Design, Enabling Reliable ...
A new study shows that combining machine learning with advanced material engineering can significantly improve the ...
A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has made strides in the theoretical design of nonlinear optical (NLO) materials by ...
Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...
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 ...
Hydrogen storage is limited by high pressure or cold tanks. Metal hydrides offer efficiency. A large curated database reveals key atomic traits to guide design. (Nanowerk News) Hydrogen fuels ...
(Nanowerk News) 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 ...
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 ...
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