Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional materials. Materials scientists are therefore working to develop and improve new ...

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 ...

Data-driven science represents a transformative paradigm in materials science. Both data-driven materials science and informatics encompass systematic knowledge extraction from materials datasets.

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.

(Nanowerk News) Nanoengineers at the University of California San Diego’s Jacobs School of Engineering have developed an AI algorithm that predicts the structure and dynamic properties of any material ...

Acelab and mindful MATERIALS are proud to announce a strategic partnership that integrates Acelab’s innovative Materials Hub platform with mindful MATERIALS’s industry-leading Common Materials ...

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 ...

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 an ...

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 ...

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 ...