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A pressure-transferable coarse-grained potential for modeling the shock Hugoniot of polyethylene

机译:用于模拟聚乙烯休克尼奥特压力的可传递压力的粗粒电势

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摘要

We investigate the thermomechanical response of semi-crystalline polyethylene under shock compression by performing molecular dynamics (MD) simulations using a new coarse-graining scheme inspired by the embedded atom method. The coarse-graining scheme combines the iterative Boltzmann inversion method and least squares optimization to parameterize interactions between coarse-grained sites, including a many-body potential energy designed to improve the representability of the model across a wide range of thermodynamic states. We demonstrate that a coarse-grained model of polyethylene, calibrated to match target structural and thermodynamic data generated from isothermal MD simulations at different pressures, can also accurately predict the shock Hugoniot response. Analysis of the rise in temperature along the shock Hugoniot and comparison with analytical predictions from the Mie-Gruneisen equation of state are performed to thoroughly explore the thermodynamic consistency of the model. As the coarse-graining model affords nearly two orders of magnitude reduction in simulation time compared to all-atom MD simulations, the proposed model can help identify how nanoscale structure in semi-crystalline polymers, such as polyethylene, influences mechanical behavior under extreme loading. Published by AIP Publishing.
机译:我们通过使用受嵌入原子方法启发的新粗粒度方案执行分子动力学(MD)模拟,研究了在冲击压缩下半结晶聚乙烯的热机械响应。粗粒度方案结合了迭代的Boltzmann反演方法和最小二乘优化,以对粗粒度位点之间的相互作用进行参数化,包括设计用于改善模型在广泛热力学状态下的可表示性的多体势能。我们证明,经过校准以匹配在不同压力下通过等温MD模拟生成的目标结构和热力学数据的聚乙烯粗粒模型也可以准确预测休格尼奥特反应。进行了沿休格尼奥特激波温度升高的分析,并与Mie-Gruneisen状态方程的分析预测进行了比较,以彻底探索模型的热力学一致性。与全原子MD模拟相比,由于粗粒度模型的模拟时间减少了近两个数量级,因此所提出的模型可以帮助识别半结晶聚合物(例如聚乙烯)中的纳米级结构如何在极端载荷下影响机械性能。由AIP Publishing发布。

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