Composition driven machine learning for unearthing high-strength lightweight multi-principal element alloys

Chee Koon Ng

Keywords: Machine learning, Bayesian optimization, Multi-principal element alloys, Effective specific hardness

TL;DR: We leveraged on a composition-driven machine learning approach, utilizing surrogate models, Bayesian Optimization and principal component analysis, to explore and exploit the vast alloy space efficiently to unearth high strength lightweight alloys.

Confirmation Of Submission Requirements: I submit a previously published paper. It was published in an archival peer–reviewed venue on or after September 8th 2024, I specify the DOI in the field below, and I submit the camera-ready version of the paper.

DOI: https://doi.org/10.1016/j.jallcom.2024.176517

Submission Number: 133