In the age of digital transformation, machine learning (ML) is rapidly becoming a pivotal technology in various sectors. One of its most exciting applications is in the field of advanced materials ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

A recent study published in npj Materials Degradation introduces a two-stage machine learning (ML) framework that predicts the degradation of protective coatings under various environmental conditions ...

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 ...

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

A recent study published in Small highlights how machine learning (ML) is reshaping the search for sustainable energy materials. Researchers introduced OptiMate, a graph attention network designed to ...

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 ...

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by University of Florida engineering professor Megan Butala enables a novel ...