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 ...

(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 ...

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.

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 ...

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 ...

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 ...

Nanoengineers have developed an AI algorithm that predicts the structure and dynamic properties of any material -- whether existing or new -- almost instantaneously. Known as M3GNet, the algorithm was ...