Moment tensor potential for static and dynamic investigations of screw dislocations in bcc Nb

IF 1.9 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY Modelling and Simulation in Materials Science and Engineering Pub Date : 2024-03-08 DOI:10.1088/1361-651x/ad2d68
Nikolay Zotov, Konstantin Gubaev, Julian Wörner, Blazej Grabowski
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Abstract

A new machine-learning interatomic potential, specifically a moment tensor potential (MTP), is developed for the study of screw-dislocation properties in body-centered-cubic (bcc) Nb in the thermally- and stress-assisted temperature regime. Importantly, configurations with straight screw dislocations and with kink pairs are included in the training set. The resulting MTP reproduces with near density-functional theory (DFT) accuracy a broad range of physical properties of bcc Nb, in particular, the Peierls barrier and the compact screw-dislocation core structure. Moreover, it accurately reproduces the energy of the easy core and the twinning-anti-twinning asymmetry of the critical resolved shear stress (CRSS). Thereby, the developed MTP enables large-scale molecular dynamics simulations with near DFT accuracy of properties such as for example the Peierls stress, the critical waiting time for the onset of screw dislocation movement, atomic trajectories of screw dislocation migration, as well as the temperature dependence of the CRSS. A critical assessment of previous results obtained with classical embedded atom method potentials thus becomes possible.
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用于静态和动态研究 bcc Nb 中螺钉位错的力矩张量势能
我们开发了一种新的机器学习原子间位势,特别是力矩张量位势(MTP),用于研究体心立方体(bcc)铌在热和应力辅助温度机制下的螺钉位错特性。重要的是,在训练集中包含了具有直螺钉位错和扭结对的构型。由此产生的 MTP 以接近密度泛函理论(DFT)的精度再现了 bcc Nb 的各种物理性质,特别是 Peierls 势垒和紧凑的螺旋位错核心结构。此外,它还精确地再现了易核心的能量和临界分辨剪切应力(CRSS)的孪生-反孪生不对称。因此,所开发的 MTP 能够以接近 DFT 的精度进行大规模分子动力学模拟,模拟的特性包括佩尔应力、螺杆位错运动开始的临界等待时间、螺杆位错迁移的原子轨迹以及 CRSS 的温度依赖性。因此,对以前用经典嵌入式原子法势能获得的结果进行批判性评估成为可能。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
96
审稿时长
1.7 months
期刊介绍: Serving the multidisciplinary materials community, the journal aims to publish new research work that advances the understanding and prediction of material behaviour at scales from atomistic to macroscopic through modelling and simulation. Subject coverage: Modelling and/or simulation across materials science that emphasizes fundamental materials issues advancing the understanding and prediction of material behaviour. Interdisciplinary research that tackles challenging and complex materials problems where the governing phenomena may span different scales of materials behaviour, with an emphasis on the development of quantitative approaches to explain and predict experimental observations. Material processing that advances the fundamental materials science and engineering underpinning the connection between processing and properties. Covering all classes of materials, and mechanical, microstructural, electronic, chemical, biological, and optical properties.
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