|About this Abstract
||2022 TMS Annual Meeting & Exhibition
||High-throughput Engineering of Oxidation Behavior in complex refectory alloys
||Daniel Sauceda, Prashant Singh, Raymundo Arroyave
|On-Site Speaker (Planned)
High-temperature mechanical response makes refractory alloys a potential candidate for replacing existing superalloys. However, the technological application of refectories is limited by severe oxidation. We present an automated machine-learning-based framework for high-throughput assessment of oxidation behavior through the evaluation of thermodynamic stability, chemical activity, reaction products (phases), phase fractions of competing phases, as well as the survivability of the parent alloys. Two extreme examples were chosen to establish the applicability of approach (i) refractory-based ceramics (MAX phases) and (ii) refractory high-entropy alloys. The predicted oxidation behavior of Ti2AlC MAX phase shows good agreement with our experiment performed on wedge samples. The proposed approach could guide the experimental discovery and optimization of structural materials with superior high-temperature performance under oxidizing conditions.
||Computational Materials Science & Engineering, Machine Learning, Other