Izvekov Sergei, Rice Betsy M
U.S. Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005, USA.
J Chem Phys. 2014 Mar 14;140(10):104104. doi: 10.1063/1.4866142.
A new bottom-up procedure for constructing non-conservative (dissipative and stochastic) interactions for dissipative particle dynamics (DPD) models is described and applied to perform hierarchical coarse-graining of a polar molecular liquid (nitromethane). The distant-dependent radial and shear frictions in functional-free form are derived consistently with a chosen form for conservative interactions by matching two-body force-velocity and three-body velocity-velocity correlations along the microscopic trajectories of the centroids of Voronoi cells (clusters), which represent the dissipative particles within the DPD description. The Voronoi tessellation is achieved by application of the K-means clustering algorithm at regular time intervals. Consistently with a notion of many-body DPD, the conservative interactions are determined through the multi-scale coarse-graining (MS-CG) method, which naturally implements a pairwise decomposition of the microscopic free energy. A hierarchy of MS-CG/DPD models starting with one molecule per Voronoi cell and up to 64 molecules per cell is derived. The radial contribution to the friction appears to be dominant for all models. As the Voronoi cell sizes increase, the dissipative forces rapidly become confined to the first coordination shell. For Voronoi cells of two and more molecules the time dependence of the velocity autocorrelation function becomes monotonic and well reproduced by the respective MS-CG/DPD models. A comparative analysis of force and velocity correlations in the atomistic and CG ensembles indicates Markovian behavior with as low as two molecules per dissipative particle. The models with one and two molecules per Voronoi cell yield transport properties (diffusion and shear viscosity) that are in good agreement with the atomistic data. The coarser models produce slower dynamics that can be appreciably attributed to unaccounted dissipation introduced by regular Voronoi re-partitioning as well as by larger numerical errors in mapping out the dissipative forces. The framework presented herein can be used to develop computational models of real liquids which are capable of bridging the atomistic and mesoscopic scales.
描述了一种用于耗散粒子动力学（DPD）模型构建非保守（耗散和随机）相互作用的自下而上的新方法，并将其应用于极性分子液体（硝基甲烷）的分层粗粒化。通过沿Voronoi单元（簇）质心的微观轨迹匹配两体力 - 速度和三体速度 - 速度相关性，以无函数形式导出与保守相互作用的选定形式一致的距离相关径向和剪切摩擦力，这些Voronoi单元代表DPD描述中的耗散粒子。通过在规则时间间隔应用K - 均值聚类算法实现Voronoi镶嵌。与多体DPD的概念一致，保守相互作用通过多尺度粗粒化（MS - CG）方法确定，该方法自然地实现微观自由能的成对分解。推导了从每个Voronoi单元一个分子到每个单元64个分子的MS - CG / DPD模型层次结构。对于所有模型，摩擦力的径向贡献似乎占主导地位。随着Voronoi单元尺寸增加，耗散力迅速局限于第一配位层。对于两个及更多分子的Voronoi单元，速度自相关函数的时间依赖性变得单调，并且相应的MS - CG / DPD模型能很好地再现。原子系综和粗粒化系综中力和速度相关性的比较分析表明，每个耗散粒子低至两个分子时就呈现马尔可夫行为。每个Voronoi单元有一个和两个分子的模型产生的输运性质（扩散和剪切粘度）与原子数据吻合良好。较粗的模型产生较慢的动力学，这可明显归因于由规则Voronoi重新划分引入的未考虑的耗散以及在映射耗散力时较大的数值误差。本文提出的框架可用于开发能够弥合原子尺度和介观尺度的真实液体计算模型。
