biostudies-literatureUnknown16(43)Hickey JCDeveloping multifunctional materials with superior mechanical properties, including high hardness and oxidation resistance, remains essential for aerospace, defense, and industrial applications. Machine learning offers a powerful, data-driven pathway for discovering new hard, oxidation-resistant materials for these uses, providing an efficient and scalable alternative to conventional materials discovery methods. Here, we present a pair of extreme gradient boosting (XGBoost) models, trained on compositional and structural descriptors. A Vickers hardness (<i>H</i> _V) model was developed using a curated dataset of 1225 while a model for predicting the oxidation temperature (<i>T</i> _p) was constructed using 348 compounds. The model was subsequently validated against a diChemical science20601-20611https://www.ebi.ac.uk/biostudies/studies/S-EPMC12506783biostudies-literatureIdentifying inorganic solids for harsh environments &lt;i&gt;via&lt;/i&gt; machine learning.PMC12506783Cuervo GArrieta RZhu PHoang SBrgoch JFlores MKarimaghaei AMHickey JCKumar AfalseIdentifying inorganic solids for harsh environments &lt;i&gt;via&lt;/i&gt; machine learning.Developing multifunctional materials with superior mechanical properties, including high hardness and oxidation resistance, remains essential for aerospace, defense, and industrial applications. Machine learning offers a powerful, data-driven pathway for discovering new hard, oxidation-resistant materials for these uses, providing an efficient and scalable alternative to conventional materials discovery methods. Here, we present a pair of extreme gradient boosting (XGBoost) models, trained on compositional and structural descriptors. A Vickers hardness (<i>H</i> _V) model was developed using a curated dataset of 1225 while a model for predicting the oxidation temperature (<i>T</i> _p) was constructed using 348 compounds. The model was subsequently validated against a di2025-01-01T00:00:00Z2025 Nov2026-06-05T12:04:50.444Z2026-05-16T03:12:35.34ZS-EPMC125067834106978810.1039/d5sc05800g