基于分子动力学与耗散粒子动力学串行耦合的面心立方金属粗粒化模型

通过全原子分子动力学(MD)与等温耗散粒子动力学(DPD)的串行耦合，提出了面心立方金属粗粒化模型的建立方法。该方法将一定数量的原子粗粒化为单个介观 DPD 粒子，假设 DPD 粒子间作用势的表达式为Sutton-Chen势函数形式，利用遗传算法，以 MD和DPD计算的单晶金属常温(298 K)等温线相一致为目标，确定了DPD粒子间作用势函数的参数。对单晶铜纳米棒的轴向拉伸开展 MD 和 DPD 对比模拟，发现在纳米棒弹性响应阶段，两者计算结果吻合较好，而屈服应力和屈服应变存在一定差距。建议在优化 DPD势函数参数时，引入更多的材料力学响应信息，进一步提高介观DPD模型的准确性。

A coarse-grained model for fcc metals based on hierarchical coupling between molecular dynamics and isothermal dissipative particle dynamics

A hierarchical coupling approach to obtaining a mesoscale model of fcc metals is developed by linking all-atom molecular dynamics (MD) to isothermal dissipative particle dynamics (DPD).The mesoscale model is constructed by coarse-graining a certain number of atoms into a DPD particle.Using a top-down method,the interaction potential for DPD particles is assumed to be of Sutton-Chen form and a genetic algorithm is used to parameterize the DPD potential by optimizing the agreement with MD predictions for the respective 298 Kisotherms.Simulations of Cu nanobars subjected to uniaxial tension using MD and DPD yield good agreement in the elastic regime,providing partial validation of the proposed hierarchical coupling approach.The DPD predictions for stress and strain at the yield point for uniaxial extension were not in close agreement with MD.Possible paths to improving the DPD model based on incorporating additional property information during the parameter optimization are suggested.