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基于原子相互作用的高熵合金相形成预测

Atomic Interaction-Based Prediction of Phase Formations in High-Entropy Alloys.

作者信息

Islam Md Tohidul, Giles Stephen A, Sengupta Debasis, Rajan Krishna, Broderick Scott R

机构信息

Department of Materials Design and Innovation, University at Buffalo, Buffalo, New York 14260, United States.

CFD Research Corporation, Huntsville, Alabama 35806, United States.

出版信息

ACS Omega. 2025 Jun 6;10(23):24560-24575. doi: 10.1021/acsomega.5c01304. eCollection 2025 Jun 17.

DOI:10.1021/acsomega.5c01304
PMID:40547667
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12177746/
Abstract

High-entropy alloys (HEAs) are of particular interest due to their unique combination of high strength, ductility, and fracture resistance. These properties are largely impacted by the phases and number of phases present in the alloy. Due to the enormous chemical design space, with typically five or six elements present in the alloys in addition to the various processing parameters, the prediction of the number of phases is challenging. While there have been multiple recent reports of phase predictions through data-driven models, an alternate approach is proposed and demonstrated here. In this work, phase prediction is performed using features derived from DFT-calculated pairwise interactions among constituent elements (incorporating bonding and structure) rather than relying solely on traditional elemental descriptors such as electronegativity. By focusing on atomic interaction features, our model provides a novel perspective on the phase stability in HEAs. This approach yields a predictive model for phase formation in HEAs that is comparable in accuracy to prior models while offering improved interpretability. By analyzing the contributions of various binary interactions to the prediction, the model provides insight into the atomic-scale factors influencing whether an alloy forms a single-phase solid solution (SS) or multiphase microstructure.

摘要

高熵合金(HEAs)因其高强度、延展性和抗断裂性的独特组合而备受关注。这些性能在很大程度上受到合金中存在的相和相数的影响。由于巨大的化学设计空间,合金中除了各种加工参数外通常还存在五种或六种元素,因此相数的预测具有挑战性。虽然最近有多个通过数据驱动模型进行相预测的报道,但本文提出并展示了一种替代方法。在这项工作中,相预测是使用从密度泛函理论(DFT)计算的组成元素之间的成对相互作用(包括键合和结构)导出的特征来进行的,而不是仅仅依赖于传统的元素描述符,如电负性。通过关注原子相互作用特征,我们的模型为高熵合金中的相稳定性提供了一个新的视角。这种方法产生了一个用于高熵合金相形成的预测模型,其准确性与先前的模型相当,同时提供了更好的可解释性。通过分析各种二元相互作用对预测的贡献,该模型深入了解了影响合金形成单相固溶体(SS)或多相微观结构的原子尺度因素。

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