Recent progress in deep learning has significantly impacted materials science, leading to accelerated material discovery and innovation. ElemNet, a deep neural network model that predicts formation ...
Exothermic Molding, Inc. (www.exothermic.com), a key partner, has leveraged NEOZANT™’s fire-retardant properties for JBT’s (www.jbtc.com) new line of autonomous vehicle tops and fronts, ensuring ...
Using a material derived from plants, researchers at Penn State have devised a renewable and sustainable approach to separating and recovering dysprosium, a heavy rare earth element used in ...
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Scientists design 2D materials with atomic precision for future devices, next-gen technologies
Scientists at the U.S. Department of Energy’s Argonne National Laboratory are pushing materials design ...
CINCINNATI--(BUSINESS WIRE)--Element Materials Technology (Element), a global leader in testing, inspection and certification (TIC) services, announces an $8m expansion in the Cincinnati region, with ...
Materials design has largely expanded to multiple compositions, which requires the mixing of an increasing number of elements. In this joint Focus issue with Nature Materials, we take a closer look at ...
A team of scientists from Ames National Laboratory has developed a new machine learning model for discovering critical-element-free permanent magnet materials. The model predicts the Curie temperature ...
A team of scientists developed a new machine learning model for discovering critical-element-free permanent magnet materials based on the predicted Curie temperature of new material combinations. A ...
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