A D V A N C E D M A T E R I A L S & P R O C E S S E S | M A R C H 2 0 2 3 1 9 Fig. 2 — Full composition prediction in the Al-Co-Cr-Fe-Ni system. (a) (b) (c) (d) (e) Fig. 3 —Screening criteria for (a) fcc and (b) bcc HEAs in the Al-Co-Cr-Fe-Ni system. With the database, Fig. 3 shows researchers’ screening results for (a) fcc and (b) bcc HEAs, sorted by phase stabilities. Screening criteria include phase stability and elastic properties. Users can add their own screening criteria to identify the HEAs that meet their specific application requirements. SUMMARY The HEA_ML helps predict the mechanical properties of HEAs and takes the guesswork out of composition choices. It also helps customers who have identified interested compositions to predict the performance of the mechanical property under high-temperature conditions. This is particularly helpful in the aerospace industry as engineers and design teams require materials that can withstand not only extreme temperatures but also harsh conditions. To sample this software tool, visit https://github.com/IMPDGroup/HEA_ ML to understand its capabilities further. ~AM&P For more information: Dr. Yu Zhong, associate professor, Worcester Polytechnic Institute, 100 Institute Rd., Worcester, MA 01609, yzhong@wpi.edu. References 1. S. Yang and Y. Zhong, Ab Initio Modeling of fcc Fe-Co-Cr-Ni High Entropy Alloys with Full Composition Range, J. Phase Equilib. Diffus., 42, p 656–672, 2021, doi.org/10.1007/ s11669-021-00905-w. 2. S. Yang, G. Liu, and Y. Zhong, Revisit the VEC Criterion in High Entropy Alloys (HEAs) with High-throughput Ab Initio Calculations: A Case Study with Al-Co-Cr-Fe-Ni System, Journal of Alloys and Compounds, Vol. 916, 2022, p 165477, doi.org/10.1016/j.jallcom. 2022.165477. (f) (a) (b)
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