Machine learning studies for magnetic compositionally complex alloys: A critical review

IF 33.6 1区材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY

Progress in Materials Science Pub Date : 2024-06-26 DOI:10.1016/j.pmatsci.2024.101332

Xin Li , Chan-Hung Shek , Peter K. Liaw , Guangcun Shan

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Abstract

Soft magnetic alloys play a critical role in power conversion, magnetic sensing, magnetic storage and electric actuating, which are fundamental components of modern technological innovation. Therefore, the rational design of soft magnetic alloys holds substantial scientific and commercial value. With excellent comprehensive performance, emerging compositionally complex alloys (CCAs) with high chemical complexity have garnered significant interest. The huge composition search space of CCAs provides both challenges and opportunities for discovering new high-performance magnetic materials. The traditional alloy design method relying on scientific intuition and a trial-and-error strategy could be inefficient and costly for magnetic CCAs. Accordingly, with great capacities for nonlinear and adaptive information processing, machine learning (ML) has shown great potential in magnetic CCA studies. This paper reviews magnetic properties of CCAs, examines the various inspiring applications of ML methods in magnetic CCAs, and discusses the future directions for unleashing the full potential of ML methods for applications in magnetic CCAs’ studies.

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磁性成分复杂合金的机器学习研究：重要综述

软磁合金在电力转换、磁感应、磁存储和电动执行等现代技术创新的基本组成部分中发挥着至关重要的作用。因此，合理设计软磁合金具有重要的科学和商业价值。新兴的高化学复杂性成分复杂合金（CCAs）具有优异的综合性能，已引起人们的极大兴趣。CCAs 巨大的成分搜索空间为发现新型高性能磁性材料提供了挑战和机遇。对于磁性 CCA 而言，依靠科学直觉和试错策略的传统合金设计方法可能效率低下、成本高昂。因此，机器学习（ML）具有强大的非线性和自适应信息处理能力，在磁性 CCA 研究中显示出巨大潜力。本文回顾了磁性 CCA 的磁特性，探讨了 ML 方法在磁性 CCA 中的各种启发性应用，并讨论了充分释放 ML 方法在磁性 CCA 研究中的应用潜力的未来方向。

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来源期刊

Progress in Materials Science 工程技术-材料科学：综合

CiteScore

59.60

自引率

0.80%

发文量

101

审稿时长

11.4 months

期刊介绍： Progress in Materials Science is a journal that publishes authoritative and critical reviews of recent advances in the science of materials. The focus of the journal is on the fundamental aspects of materials science, particularly those concerning microstructure and nanostructure and their relationship to properties. Emphasis is also placed on the thermodynamics, kinetics, mechanisms, and modeling of processes within materials, as well as the understanding of material properties in engineering and other applications. The journal welcomes reviews from authors who are active leaders in the field of materials science and have a strong scientific track record. Materials of interest include metallic, ceramic, polymeric, biological, medical, and composite materials in all forms. Manuscripts submitted to Progress in Materials Science are generally longer than those found in other research journals. While the focus is on invited reviews, interested authors may submit a proposal for consideration. Non-invited manuscripts are required to be preceded by the submission of a proposal. Authors publishing in Progress in Materials Science have the option to publish their research via subscription or open access. Open access publication requires the author or research funder to meet a publication fee (APC). Abstracting and indexing services for Progress in Materials Science include Current Contents, Science Citation Index Expanded, Materials Science Citation Index, Chemical Abstracts, Engineering Index, INSPEC, and Scopus.