Revealing interstitial energetics in Ti-23Nb-0.7Ta-2Zr gum metal base alloy via universal machine learning interatomic potentials

This article reports on the use of machine learning to study the energetics of interstitial atoms in a specific alloy (Ti-23Nb-0.7Ta-2Zr). The focus is on using universal machine learning interatomic potentials, suggesting an advanced computational approach to materials science. The title indicates a research paper, likely detailing the methodology, results, and implications of this analysis.