论文标题
导航高渗透合金的复杂成分景观
Navigating the Complex Compositional Landscape of High-Entropy Alloys
论文作者
论文摘要
在高维成分空间中存在的高渗透合金为实现前所未有的结构和功能特性提供了巨大的独特机会。但是，一个基本的挑战在于如何准确预测特定的合金阶段和理想的特性。这篇评论文章概述了迄今为止发布的数据驱动方法，以解决设计高渗透合金的这一指数问题。描述了经验参数，第一原理和热力学计算，统计方法和机器学习的各种利用。在另一种方法中，展示了使用现象学特征和数据启发的自适应特征在预测高渗透固体溶液阶段和金属合金复合材料时的有效性。鉴于熵效应，高渗透合金作为具有改进特性的新型功能材料的前景。讨论了当前高渗透合金设计的成功，挑战和局限性，并提出了一些合理的未来方向。
High-entropy alloys, which exist in the high-dimensional composition space, provide enormous unique opportunities for realizing unprecedented structural and functional properties. A fundamental challenge, however, lies in how to predict the specific alloy phases and desirable properties accurately. This review article provides an overview of the data-driven methods published to date to tackle this exponentially hard problem of designing high-entropy alloys. Various utilizations of empirical parameters, first-principles and thermodynamic calculations, statistical methods, and machine learning are described. In an alternative method, the effectiveness of using phenomenological features and data-inspired adaptive features in the prediction of the high-entropy solid solution phases and intermetallic alloy composites is demonstrated. The prospect of high-entropy alloys as a new class of functional materials with improved properties is featured in light of entropic effects. The successes, challenges, and limitations of the current high-entropy alloys design are discussed, and some plausible future directions are presented.
