FAYETTEVILLE, GA, UNITED STATES, March 20, 2026 /EINPresswire.com/ -- Using machine learning regression models, we ...

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 ...

Computer simulations and artificial intelligence often make significant errors when predicting the properties of new, high-performance materials, according to a new international study led by the ...

Research shows that combining silica fume, fly ash, and manufactured sand in concrete significantly boosts strength and enhances predictive modeling accuracy.

MLIP calculations successfully identify suitable dopants for a novel photocatalytic material, report researchers from the ...

Two-dimensional (2D) materials have shown extraordinary potential in electrocatalytic reactions due to their unique structural and electronic properties. In a new review published in AI Mater., first ...

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...

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 ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits, and suddenly, a molecule makes a promising new medicine. Normally, creating better ...