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Molecular dynamics is a powerful simulation tool to explore material properties. Most of the realistic material systems are too large to be simulated with first-principles molecular dynamics. Classical molecular dynamics has lower…

Computational Physics · Physics 2021-01-11 Zun Wang , Chong Wang , Sibo Zhao , Shiqiao Du , Yong Xu , Bing-Lin Gu , Wenhui Duan

Simulating large proteins using traditional molecular dynamics (MD) is computationally demanding. To address this challenge, we propose a novel tree-structured coarse-grained model that efficiently captures protein dynamics. By leveraging a…

Chemical Physics · Physics 2024-12-11 Jinzhen Zhu

This work presents a novel framework governing the development of an efficient, accurate, and transferable coarse-grained (CG) model of a polyether material. The proposed framework combines the two fundamentally different classical…

Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampling molecular configurations of interest can be done…

Computational Physics · Physics 2022-11-30 Kirill Shmilovich , Marc Stieffenhofer , Nicholas E. Charron , Moritz Hoffmann

Coarse-grained (CG) molecular simulations have become a standard tool to study molecular processes on time- and length-scales inaccessible to all-atom simulations. Parameterizing CG force fields to match all-atom simulations has mainly…

Computational Physics · Physics 2023-02-07 Jonas Köhler , Yaoyi Chen , Andreas Krämer , Cecilia Clementi , Frank Noé

A molecule's geometry, also known as conformation, is one of a molecule's most important properties, determining the reactions it participates in, the bonds it forms, and the interactions it has with other molecules. Conventional…

Machine Learning · Computer Science 2020-01-01 Elman Mansimov , Omar Mahmood , Seokho Kang , Kyunghyun Cho

We formulate an effective-description framework for the dynamics of open quantum systems by extending the time-coarse-graining formalism to open systems. Our coarse-graining procedure efficiently removes high-frequency processes which are…

Quantum Physics · Physics 2018-01-17 Chang-Woo Lee , Changsuk Noh , Jaewan Kim

We poorly understand the macroscopic properties of complex fluids and of amorphous bodies in general. This is mainly due to the interplay between phenomena at different levels and length-scales. In particular, it is not necessarily true…

Soft Condensed Matter · Physics 2010-04-14 Alessio Zaccone

Complex fluids exhibit structure on a wide range of length and time scales, and hierarchical approaches are necessary to investigate all facets of their often unusual properties. The study of idealized coarse-grained models at different…

Soft Condensed Matter · Physics 2008-10-23 Friederike Schmid

One key factor that limits the predictive power of molecular dynamics simulations is the accuracy and transferability of the input force field. Force fields are challenged by heterogeneous environments, where electronic responses give rise…

Chemical Physics · Physics 2016-09-13 Flaviu S. Cipcigan , Vlad P. Sokhan , Jason Crain , Glenn J. Martyna

We present a computer-assisted approach to coarse-graining the evolutionary dynamics of a system of nonidentical oscillators coupled through a (fixed) network structure. The existence of a spectral gap for the coupling network graph…

Statistical Mechanics · Physics 2015-05-28 Karthikeyan Rajendran , Ioannis G. Kevrekidis

This review is a tutorial for scientists interested in the problem of protein structure prediction, particularly those interested in using coarse-grained molecular dynamics models that are optimized using lessons learned from the energy…

Biomolecules · Quantitative Biology 2014-01-06 N. P. Schafer , B. L. Kim , W. Zheng , P. G. Wolynes

We propose and illustrate an approach to coarse-graining the dynamics of evolving networks (networks whose connectivity changes dynamically). The approach is based on the equation-free framework: short bursts of detailed network evolution…

Social and Information Networks · Computer Science 2012-02-28 Katherine A. Bold , Karthikeyan Rajendran , Balázs Ráth , Ioannis G. Kevrekidis

Machine-learned (ML) coarse-grained (CG) models are a promising tool for significantly enhancing the efficiency of molecular simulations by systematically removing degrees of freedom while retaining fidelity to the underlying fine-grained…

Chemical Physics · Physics 2026-02-27 Patrick G. Sahrmann , Benjamin T. Nebgen , Kipton Barros , Brenden W. Hamilton

Coarse-graining (CG) accelerates molecular simulations of protein dynamics by simulating sets of atoms as singular beads. Backmapping is the opposite operation of bringing lost atomistic details back from the CG representation. While…

Machine Learning · Computer Science 2023-03-06 Soojung Yang , Rafael Gómez-Bombarelli

Partitioned cellular automata are known to be an useful tool to simulate linear and nonlinear problems in physics, specially because they allow for a straightforward way to define conserved quantities and reversible dynamics. Here we show…

Cellular Automata and Lattice Gases · Physics 2020-12-17 Pedro C. S. Costa , Fernando de Melo

Folding and aggregation of proteins, the interaction between proteins and membranes, as well as the adsorption of organic soft matter to inorganic solid substrates belong to the most interesting challenges in understanding structure and…

Soft Condensed Matter · Physics 2007-12-06 Michael Bachmann , Wolfhard Janke

Identifying the relevant coarse-grained degrees of freedom in a complex physical system is a key stage in developing powerful effective theories in and out of equilibrium. The celebrated renormalization group provides a framework for this…

Statistical Mechanics · Physics 2024-11-27 Doruk Efe Gökmen , Zohar Ringel , Sebastian D. Huber , Maciej Koch-Janusz

We report on a molecular dynamics investigation of the wetting properties of graphitic surfaces by various solutions at concentrations 1-8 wt% of commercially available non-ionic surfactants with long hydrophilic chains, linear or T-shaped.…

Chemical Physics · Physics 2012-09-12 Danilo Sergi , Giulio Scocchi , Alberto Ortona

Coarse graining techniques offer a promising alternative to large-scale simulations of complex dynamical systems, as long as the coarse-grained system is truly representative of the initial one. Here, we investigate how the dynamical…

Disordered Systems and Neural Networks · Physics 2009-11-13 David Gfeller , Paolo De Los Rios