45 citations · 51 across the 3 of their papers we have counts for
3 papers · 1 filter
Decoratypes: An Extensible Crystal Taxonomy for Machine Learning-Guided Materials Discovery
Kyle D. Miller, Michele Campbell, Danilo Puggioni +1
We introduce decoratypes as a structure taxonomy that classifies compounds based on site decorations of specific structural prototypes. Building on this foundation, a ferroelectric…
Machine learning the electronic structure of matter across temperatures
Lenz Fiedler, Normand A. Modine, Kyle D. Miller +1
We introduce machine learning (ML) models that predict the electronic structure of materials across a wide temperature range. Our models employ neural networks and are trained on d…
Database, Features, and Machine Learning Model to Identify Thermally Driven Metal-Insulator Transition Compounds
Alexandru B. Georgescu, Peiwen Ren, Aubrey R. Toland +6
Metal-insulator transition (MIT) compounds are materials that may exhibit insulating or metallic behavior, depending on the physical conditions, and are of immense fundamental inte…