Litcius/Paper detail

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Giuseppe Bianco, Ambreen Nisar, Cheng Zhang, Benjamin Boesl, Arvind Agarwal

2022Ceramics International19 citationsDOIOpen Access PDF

Topics & Concepts

Materials scienceMicrostructureOxidizing agentOxideScale (ratio)CeramicComposite materialMetallurgyChemistryOrganic chemistryPhysicsQuantum mechanicsAdvanced ceramic materials synthesisAdvanced materials and compositesNuclear Materials and Properties
Predicting oxidation damage in ultra high-temperature borides: A machine learning approach | Litcius