Data-driven prediction of thin-film metallic glass forming ability via Bayesian classification and experimental verification in the Cu–Zr–Al system
Identifying alloy compositions suitable for metallic glass formation from the vast and multi-dimensional space of elemental combinations remains a significant challenge. In the present study, we develop—using literature data—a Bayesian machine learning model based on Gaussian process classification for predicting the g...