Accurate prediction of materials phase diagrams from first principles remains a central challenge in computational materials science. Machine-learning interatomic potentials can provide near-DFT ...

The alternative text for this image may have been generated using AI. The question then arises whether a cheaper surrogate model can replace DFT in predictions of stable materials. In recent years, ...

Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...