Ankit Roy, a doctoral candidate in the Department of Mechanical Engineering and Mechanics, has been selected as a recipient of an Acta Student Award for his research on high-entropy alloys (HEAs).
The award recognizes Roy’s contributions to the article, “Machine learned feature identification for predicting phase and Young's modulus of low-, medium- and high-entropy alloys,” published in the August 2020 issue of Scripta Materialia. Machine learning has emerged as a potential tool to rapidly accelerate the discovery of novel materials, due to its rapidity, scalability, and now, reasonably accurate material property predictions. In the present work, Roy et al. implement machine learning tools to predict the crystallographic phase and Young’s modulus of low-, medium- and high entropy alloys.
The decision committee, which selects up to 16 Acta Student Award recipients (four for each of the Acta journals) annually, deemed that the paper demonstrated “exceptional value to the materials community” and also recognized Roy’s exemplary personal credentials and recommendations.
The award will be formally presented at the Acta Symposium during the TMS 2022 conference (Feb. 27-Mar. 3, 2022) in Anaheim, California.
