6533b833fe1ef96bd129b9a4
RESEARCH PRODUCT
Introducing Memory in Coarse-Grained Molecular Simulations
Friederike SchmidNico F. A. Van Der VegtGerhard JungViktor KlippensteinMadhusmita Tripathysubject
010304 chemical physicsComputer scienceMarkov processEquations of motionContext (language use)Statistical mechanics010402 general chemistry01 natural sciencesField (computer science)0104 chemical sciencesSurfaces Coatings and Filmssymbols.namesakeSimple (abstract algebra)0103 physical sciencesMaterials ChemistrysymbolsStatistical physicsLimit (mathematics)Physical and Theoretical ChemistryFocus (optics)description
[Image: see text] Preserving the correct dynamics at the coarse-grained (CG) level is a pressing problem in the development of systematic CG models in soft matter simulation. Starting from the seminal idea of simple time-scale mapping, there have been many efforts over the years toward establishing a meticulous connection between the CG and fine-grained (FG) dynamics based on fundamental statistical mechanics approaches. One of the most successful attempts in this context has been the development of CG models based on the Mori–Zwanzig (MZ) theory, where the resulting equation of motion has the form of a generalized Langevin equation (GLE) and closely preserves the underlying FG dynamics. In this Review, we describe some of the recent studies in this regard. We focus on the construction and simulation of dynamically consistent systematic CG models based on the GLE, both in the simple Markovian limit and the non-Markovian case. Some recent studies of physical effects of memory are also discussed. The Review is aimed at summarizing recent developments in the field while highlighting the major challenges and possible future directions.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-05-13 |