As AI's integration in the process of designing and improving industrial infrastructure progresses, governance needs to ...
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AI-designed steel for 3D printing aims to be stronger and rust-proof
A team of researchers has used machine learning to design a new stainless steel alloy built specifically for 3D printing, one ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
Researchers from the University of South China and Purdue University have developed ultra-high strength, high-ductility steel ...
A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of ...
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 ...
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 ...
More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...
Two-dimensional (2D) materials have shown extraordinary potential in electrocatalytic reactions due to their unique structural and electronic properties. In a new review published in AI Mater., first ...
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