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cond-mat.mtrl-sci2024
Assessing data-driven predictions of band gap and electrical conductivity for transparent conducting materials
Federico Ottomano, John Y. Goulermas, Vladimir Gusev +14
Machine Learning (ML) has offered innovative perspectives for accelerating the discovery of new functional materials, leveraging the increasing availability of material databases.…
cond-mat.mtrl-sci2024
Learning Atoms from Crystal Structure
Andrij Vasylenko, Dmytro Antypov, Sven Schewe +4
Computational modelling of materials using machine learning, ML, and historical data has become integral to materials research. The efficiency of computational modelling is strongl…