Russian School of Mathematics, North Bethesda, Maryland 20852, United States.
Department of Chemical and Biological Engineering, Drexel University, Philadelphia, Pennsylvania 19104, United States.
J Chem Theory Comput. 2021 Feb 9;17(2):1045-1059. doi: 10.1021/acs.jctc.0c01003. Epub 2021 Jan 29.
Recently, a novel type of multiscale simulation, called Relative Resolution (RelRes), was introduced. In a single system, molecules switch their resolution in terms of their relative separation, with near neighbors interacting via fine-grained potentials yet far neighbors interacting via coarse-grained potentials; notably, these two potentials are analytically parametrized by a multipole approximation. This multiscale approach is consequently able to correctly retrieve across state space the structural and thermal, as well as static and dynamic, behavior of various nonpolar mixtures. Our current work focuses on the practical implementation of RelRes in LAMMPS, specifically for the commonly used Lennard-Jones potential. By examining various correlations and properties of several alkane liquids, including complex solutions of alternate cooligomers and block copolymers, we confirm the validity of this automated LAMMPS algorithm. Most importantly, we demonstrate that this RelRes implementation gains almost an order of magnitude in computational efficiency, as compared with conventional simulations. We thus recommend this novel LAMMPS algorithm for anyone studying systems governed by Lennard-Jones interactions.
最近，一种新型的多尺度模拟方法，称为相对分辨率（RelRes），被引入。在单个系统中，分子根据它们的相对分离来切换分辨率，近邻通过细粒度的势相互作用，而远邻通过粗粒度的势相互作用；值得注意的是，这两种势可以通过多极近似进行解析参数化。因此，这种多尺度方法能够正确地在状态空间中恢复各种非极性混合物的结构和热、静态和动态行为。我们目前的工作重点是在 LAMMPS 中实现 RelRes 的实际应用，特别是针对常用的 Lennard-Jones 势。通过检查几种烷烃液体的各种相关性和性质，包括交替冷却剂和嵌段共聚物的复杂溶液，我们验证了这种自动化 LAMMPS 算法的有效性。最重要的是，我们证明与传统模拟相比，这种 RelRes 实现的计算效率提高了近一个数量级。因此，我们推荐将这种新的 LAMMPS 算法用于研究 Lennard-Jones 相互作用控制的系统的任何人。
