Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...

From 11.5 million alloy candidates to AI-guided perovskites, this piece unpacks how materials informatics is speeding up ...

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 ...

A research team led by NIMS has, for the first time, produced nanoscale images of two key features in an ultra-thin material: twist domains (areas where one atomic layer is slightly rotated relative ...

BUFFALO, N.Y. – Companies face unprecedented challenges in the current economy: rising costs, directives to minimize waste and toxicity, and difficulty with leveraging data to effectively inform ...

For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...