Intelligent dissipative particle dynamics: bridging mesoscopic models from microscopic simulations via deep neural networks

DOI10.1016/J.JCP.2022.111857OpenAlexW4311903992MaRDI QIDQ2683077

Baocai Jing, Dingyi Pan, Ting Ye

Publication date: 3 February 2023

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2022.111857

zbMATH Keywords

molecular dynamicscoarse grainingdissipative particle dynamicsdeep neural network

Mathematics Subject Classification ID

Basic methods in fluid mechanics (76Mxx) Time-dependent statistical mechanics (dynamic and nonequilibrium) (82Cxx) Physiological, cellular and medical topics (92Cxx)

Uses Software

• Adam
• DeePMD-kit
• DL_MESO

Cites Work

• Dissipative particle dynamics (DPD): an overview and recent developments
• Systematic coarse-graining of spectrin-level red blood cell models
• A note on hydrodynamics from dissipative particle dynamics
• Fast parallel algorithms for short-range molecular dynamics
• Stochastic modelling: replacing fast degrees of freedom by noise
• An Averaging Principle for Fast Degrees of Freedom Exhibiting Long-Term Correlations
• LATTICE BOLTZMANN METHOD FOR FLUID FLOWS
• Transport, Collective Motion, and Brownian Motion
• The Art of Molecular Dynamics Simulation

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