Abstract
The aim of this work was to provide a guidance to the prediction and design of high-entropy alloys with good performance. New promising compositions of refractory high-entropy alloys with the desired phase composition and mechanical properties (yield strength) have been predicted using a combination of machine learning, phenomenological rules and CALPHAD modeling. The yield strength prediction in a wide range of temperatures (20–800 °C) was made using a surrogate model based on a support-vector machine algorithm. The yield strength at 20 °C and 600 °C was predicted quite precisely (the average prediction error was 11% and 13.5%, respectively) with a decrease in the precision to slightly higher than 20% at 800 °C. An Al13Cr12Nb20Ti20V35 alloy with an excellent combination of ductility and yield strength at 20 °C (16.6% and 1295 MPa, respectively) and at 800 °C (more 50% and 898 MPa, respectively) was produced based on the prediction.
Highlights
High entropy alloys (HEAs), which are sometimes called multi-principal element alloys, were originally discovered by Yeh [1] and Cantor [2]
Vanadium, zirconium, and niobium a parabolic law was observed for the dependence of specific yield strength on the content of elements
The use of a combination of calculation of phase diagrams (CALPHAD) and phenomenological rules does not result in an accurate prediction of the phase composition of the alloys; only one of them had a desirable single-phase structure
Summary
High entropy alloys (HEAs), which are sometimes called multi-principal element alloys, were originally discovered by Yeh [1] and Cantor [2]. Various approaches can be used to predict the constituted phases as a function of the chemical composition, including the phenomenological rules [16,17,18,19,20,21,22,23,24,25], calculation of phase diagrams (CALPHAD) approach [26,27,28,29,30], machine learning algorithms [31,32,33], and other computational methods such as ab initio, Monte-Carlo (MC) or molecular dynamics calculation (MD) [34,35,36,37] Each of these approaches has its own strengths and weaknesses
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