Grain-size dependence of mechanical properties in polycrystalline boron-nitride: a computational study

文献信息

发布日期 2015-07-28
DOI 10.1039/C5CP03460D
影响因子 3.676
作者

Matthew Becton, Xianqiao Wang


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摘要

The field of research in polycrystalline hexagonal boron nitride (PBN) has been enjoying extraordinary growth recently, in no small part due to the rise of graphene and the technical advancement of mass production in polycrystalline 2D materials. However, as the grain size in 2D materials can strongly affect their materials properties and the performance of their relevant devices, it is highly desirable to investigate this effect in PBN and leverage the service capability of PBN-based devices. Here we employ molecular dynamics simulations to explore the effects of grain size in PBN on its mechanical properties such as Young's modulus, yield strength, toughness, and energy release rate as well as its failure mechanism. By visualizing and comparing the tensile failure of PBN with and without a predefined crack we have shown that the grain size of PBN is positively correlated with its elastic modulus, yield strength and toughness. Through inclusion of a crack with varying length in the PBN samples, the energy release rate is determined for each grain size of PBN and it is concluded that the energy release rate increases with an increase in the average grain size of PBN. These findings offer useful insights into utilizing PBN for mechanical design in composite materials, abrasion resistance, and electronic devices etc.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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