4.7 Review

Review of high-throughput computational design of Heusler alloys

Journal

JOURNAL OF ALLOYS AND COMPOUNDS
Volume 867, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jallcom.2021.158854

Keywords

Heusler; High-throughput; DFT; Machine learning; Spintronic; Thermoelectric

Funding

  1. Academic Senate General Campus Research Grant Committee at University of California San Diego

Ask authors/readers for more resources

Heusler compounds, a large family of intermetallic compounds, provide a broad playground for novel materials design. High-throughput computational design has emerged as an efficient approach to search for target materials with desired properties, and potential future research directions in the field are discussed.
As one large family of intermetallic compounds, Heusler compounds offer a wide playground for novel materials design because of their wide range of compositions and tunable materials properties. In recent years, the high-throughput computational design has emerged as one efficient approach to search for target materials with desired properties thanks to the development of the automatic framework for materials discovery and open-access quantum materials database. In this article, we present a review of the current research progress of the high-throughput computational design of Heusler-based functional materials, including the selection of appropriate materials descriptors and common methods for evaluating materials stability, along with comprehensive lists of the predicated Heusler compounds with various types of target properties. We conclude the review with a discussion of the potential future research directions in the field. (C) 2021 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available