284 citations · 363 across the 6 of their papers we have counts for
3 papers · 1 filter
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.…
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…
Epitaxial growth, optical and electrical conductivity of the metallic pyrochlore BiRuO on Y-stabilized ZrO substrate
Marita O'Sullivan, Jonathan Alaria, Mike W. Gaultois +3
We report on the epitaxial growth, structural and electrical properties of metallic pyrochlore bismuth ruthenate heterostructures grown along both the [001] and [111] directions. O…