A novel machine learning model for the characterization of material surfaces

Machine learning (ML) enables the accurate and efficient computation of fundamental electronic properties of binary and ternary oxide surfaces, as shown by scientists from Tokyo Tech. Their ML-based model could be extended to other compounds and properties. The findings, published in the Journal of the American Chemical Society, could aid in the screening of surface properties of materials as well as in the development of functional materials.