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Title: Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys
Abstract

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature,Tbreak, introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay belowTbreak. We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.

 
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Award ID(s):
1809640
NSF-PAR ID:
10305336
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Nature Publishing Group
Date Published:
Journal Name:
npj Computational Materials
Volume:
7
Issue:
1
ISSN:
2057-3960
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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