Accession Number:

AD1105742

Title:

Materials Informatics for the Screening of Multi-Principal Elements and High-Entropy Alloys

Descriptive Note:

Journal Article - Open Access

Corporate Author:

Lehigh University Bethlehem United States

Personal Author(s):

• Rickman,J. M.
• Chan,H. M.
• Harmer,M. P.
• Smeltzer,J. A.
• Marvel,C. J.
• Roy,A.
• Balasubramanian,G.

Report Date:

2019-06-13

Pagination or Media Count:

10.0

Abstract:

The field of multi-principal element or single-phase high-entropy HE alloys has recently seen exponential growth as these systems represent a paradigm shift in alloy development, in some cases exhibiting unexpected structures and superior mechanical properties. However,the identification of promising HE alloys presents a daunting challenge given the associated vastness of the chemistrycomposition space. We describe here a supervised learning strategy for the efficient screening of HE alloys that combines two complementary tools, namely 1 a multiple regression analysis and its generalization, a canonical-correlation analysis CCA and 2 a genetic algorithm GA with a CCA-inspired fitness function. These tools permit the identification of promising multi-principal element alloys. We implement this procedure using a database for which mechanical property information exists and highlight new alloys having high hardnesses. Our methodology is validated by comparing predicted hardnesses with alloys fabricated by arc-melting, identifying alloys having very high measured hardnesses.

Descriptors:

• alloys
• entropy
• genetic algorithms
• functions (mathematics)
• correlation analysis
• regression analysis
• spectroscopy
• microstructure
• hardness

Subject Categories:

• Properties of Metals and Alloys
• Statistics and Probability
• Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE