For the U.S. Army Reserve’s 88th Readiness Division, the best way to effectively manage hazardous materials inventories and provide immediate access to safety data sheets came down to a simple choice: ...
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âš¡ An AI identifies thousands of materials to replace rare earths
Could our smartphones and electric cars one day do without rare earths, which are widely used in the design of batteries and electric motors? A team from the University of New Hampshire offers ...
A massive new database of dielectric material properties could speed up the development of electronics like smartphones and energy storage systems. AI-driven materials discovery has great potential to ...
Waste analytics company Greyparrot has launched Deepnest, an artificial intelligence- (AI-) powered waste intelligence platform designed to give brands direct access to their recyclable material data.
Data-driven science represents a transformative paradigm in materials science. Both data-driven materials science and informatics encompass systematic knowledge extraction from materials datasets.
The National Institute for Materials Science (NIMS) has been developing the DICE materials data platform* 1 to fulfill its role as a data core center in the MEXT-led project to develop materials DX ...
New technology often calls for new materials -- and with supercomputers and simulations, researchers don't have to wade through inefficient guesswork to invent them from scratch. New technology often ...
Researchers have developed a digital laboratory (dLab) system that fully automates the material synthesis and structural, physical property evaluation of thin-film samples. With dLab, the team can ...
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