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 ...

The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...

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

Explore how AI is transforming advanced materials design by analyzing microscopy images to create smarter, faster innovation ...

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 ...

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 ...

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...

MIT researchers have designed a printable aluminum alloy that’s five times stronger than cast aluminum and holds up at ...

Superconductors sit at the heart of some of the most ambitious technologies on the horizon, from lossless power grids to ...

Hydrogen peroxide is widely used but energy-intensive to produce. A new machine-learning framework helps find catalysts that ...