|About this Abstract
||2018 TMS Annual Meeting & Exhibition
||Computational Materials Discovery and Optimization
||Minimal Addition of Cerium for Stability of Critical Phases in Hard Magnetic AlNiCo Alloys: Combined Machine Learning and CALPHAD
||George S Dulikravich, Rajesh Jha
|On-Site Speaker (Planned)
This work focuses on design optimization the chemistry of AlNiCo magnetic alloys to simultaneously extremize their multiple bulk properties. We used artificial intelligence algorithms, response surfaces and multi-objective optimization algorithms. Then, we studied the phase transformations in this system by CALPHAD approach. From meta-modeling we also identified the elements that had negligible effects on the bulk properties. We replaced these non-effective alloying elements with minimal amounts of a non-critical rare-earth element, Cerium, and studied the effect of addition of Cerium on variation of critical phases responsible for superior magnetic properties through CALPHAD approach. We used TCFE9 database in Thermocalc to perform these calculations as Cerium is included in this database. Alloy compositions used in this study are experimentally verified, and the compositions were generated by application of statistical models that are well known and accepted by researchers. Application of CALPHAD and optimization using experimental databases is applicable to arbitrary alloys.
||Planned: Supplemental Proceedings volume