Rheological characterization of CuZr metallic glasses at the atomic scale

IF 2.5 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2025-02-13 DOI:10.1007/s00894-025-06307-w
Nicolás Amigo
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引用次数: 0

Abstract

Context

Understanding the shear response of metallic glasses is essential for predicting their mechanical performance and plasticity. Cu\(_{100-x}\)Zr\(_x\) metallic glasses, in particular, exhibit complex shear-thinning behavior governed by atomic composition. Prior studies have highlighted the role of composition in influencing mechanical properties; however, the relationship between the structural characteristics of these alloys and their rheological behavior requires further investigation. This work focuses on the effects of Cu content on the plastic flow of CuZr metallic glasses, emphasizing how atomic-scale features influence yield stress, viscosity, and the onset of plasticity.

Methods

Molecular dynamics simulations using the embedded atom method potential in LAMMPS were conducted to study Cu\(_{100-x}\)Zr\(_x\) metallic glasses. Samples were equilibrated at 2000 K and quenched to 300 K at 10\(^{11}\) K/s. Shear tests at six rates (\(5 \times 10^{7}\) to \(1 \times 10^{10}\) s\(^{-1}\)) were performed at 300 K, with the flow stress modeled using the Herschel-Bulkley equation. Structural features were analyzed via Voronoi polyhedra, focusing on local five-fold symmetry and liquid-like polyhedra populations. Visualization and data analysis were conducted using OVITO and Scikit-learn library for the Python programming language.

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CuZr金属玻璃在原子尺度上的流变性能
了解金属玻璃的剪切响应对于预测其力学性能和塑性至关重要。特别是Cu \(_{100-x}\) Zr \(_x\)金属玻璃,表现出受原子组成控制的复杂剪切减薄行为。先前的研究强调了成分在影响力学性能方面的作用;然而,这些合金的结构特征与流变行为之间的关系还有待进一步研究。本研究的重点是Cu含量对CuZr金属玻璃塑性流动的影响,强调原子尺度特征如何影响屈服应力、粘度和塑性的开始。方法采用嵌入原子法在LAMMPS中对Cu \(_{100-x}\) Zr \(_x\)金属玻璃进行了分子动力学模拟。样品在2000 K下平衡,在10 \(^{11}\) K/s下淬火至300 K。在300 K下进行了六种速率(\(5 \times 10^{7}\)至\(1 \times 10^{10}\) s \(^{-1}\))的剪切试验,并使用Herschel-Bulkley方程建立了流动应力模型。通过Voronoi多面体分析结构特征,重点分析局部五重对称和液体状多面体种群。使用OVITO和Python编程语言Scikit-learn库进行可视化和数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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