A comparative study of coarse-graining methods for polymeric fluids: Mori-Zwanzig vs. iterative Boltzmann inversion vs. stochastic parametric optimization

Li, Zhen; Bian, Xin; Yang, Xiu; Karniadakis, George Em

doi:10.1063/1.4959121

Title: A comparative study of coarse-graining methods for polymeric fluids: Mori-Zwanzig vs. iterative Boltzmann inversion vs. stochastic parametric optimization

Journal Article · Mon Jul 25 00:00:00 EDT 2016 · Journal of Chemical Physics

DOI:https://doi.org/10.1063/1.4959121· OSTI ID:1356514

^[1];

^[1]; Yang, Xiu ^[2]; Karniadakis, George Em ^[1]

Brown Univ., Providence, RI (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

We construct effective coarse-grained (CG) models for polymeric fluids by employing two coarse-graining strategies. The first one is a forward-coarse-graining procedure by the Mori-Zwanzig (MZ) projection while the other one applies a reverse-coarse-graining procedure, such as the iterative Boltzmann inversion (IBI) and the stochastic parametric optimization (SPO). More specifically, we perform molecular dynamics (MD) simulations of star polymer melts to provide the atomistic fields to be coarse-grained. Each molecule of star polymer with internal degrees of freedom is coarsened into a single CG particle and the effective interactions between CG particles can be either evaluated directly from microscopic dynamics based on the MZ formalism, or obtained by the reverse methods, i.e., IBI and SPO. The forward procedure has no free parameters to tune and recovers the MD system faithfully. For the reverse procedure, we find that the parameters in CG models are not interchangeable. If the free parameters are properly selected, the reverse CG procedure also yields an effective potential. Furthermore, we explain how an aggressive coarse-graining procedure introduces many-body effect, which makes the pairwise potential invalid for the same system at densities away from the training point. From this work, general guidelines for coarse-graining of polymeric fluids can be drawn.

View Accepted Manuscript (DOE)

View Accepted Manuscript (Publisher)

Cite

Export

Save

Research Organization:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division

Grant/Contract Number:: AC05-76RL01830; W911NF-12-2-0023; AC02-06CH11357; AC05-00OR22725

OSTI ID:: 1356514

Alternate ID(s):: OSTI ID: 1272642

Report Number(s):: PNNL-SA-116567; KJ0401000

Journal Information:: Journal of Chemical Physics, Vol. 145, Issue 4; ISSN 0021-9606

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 37 works

Citation information provided by
Web of Science

References (51)

Simulating Microscopic Hydrodynamic Phenomena with Dissipative Particle Dynamics Hoogerbrugge, P. J.; Koelman, J. M. V. A. Europhysics Letters (EPL), Vol. 19, Issue 3 https://doi.org/10.1209/0295-5075/19/3/001	journal	June 1992
Mori–Zwanzig formalism as a practical computational tool Hijón, Carmen; Español, Pep; Vanden-Eijnden, Eric Faraday Discuss., Vol. 144 https://doi.org/10.1039/B902479B	journal	January 2010
Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation Lei, H.; Yang, X.; Zheng, B. Multiscale Modeling & Simulation, Vol. 13, Issue 4 https://doi.org/10.1137/140981587	journal	January 2015
Multiscale coarse graining of liquid-state systems Izvekov, Sergei; Voth, Gregory A. The Journal of Chemical Physics, Vol. 123, Issue 13 https://doi.org/10.1063/1.2038787	journal	October 2005
Rheology, Microstructure and Migration in Brownian Colloidal Suspensions Pan, Wenxiao; Caswell, Bruce; Karniadakis, George Em Langmuir, Vol. 26, Issue 1 https://doi.org/10.1021/la902205x	journal	January 2010
GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation Hess, Berk; Kutzner, Carsten; van der Spoel, David Journal of Chemical Theory and Computation, Vol. 4, Issue 3 https://doi.org/10.1021/ct700301q	journal	February 2008
Role of Repulsive Forces in Determining the Equilibrium Structure of Simple Liquids Weeks, John D.; Chandler, David; Andersen, Hans C. The Journal of Chemical Physics, Vol. 54, Issue 12 https://doi.org/10.1063/1.1674820	journal	June 1971
Hydrodynamics from dissipative particle dynamics Español, Pep Physical Review E, Vol. 52, Issue 2 https://doi.org/10.1103/PhysRevE.52.1734	journal	August 1995
Dissipative particle dynamics: Bridging the gap between atomistic and mesoscopic simulation Groot, Robert D.; Warren, Patrick B. The Journal of Chemical Physics, Vol. 107, Issue 11 https://doi.org/10.1063/1.474784	journal	September 1997
Adaptive resolution molecular-dynamics simulation: Changing the degrees of freedom on the fly Praprotnik, Matej; Delle Site, Luigi; Kremer, Kurt The Journal of Chemical Physics, Vol. 123, Issue 22 https://doi.org/10.1063/1.2132286	journal	December 2005
Coarse-Graining Methods for Computational Biology Saunders, Marissa G.; Voth, Gregory A. Annual Review of Biophysics, Vol. 42, Issue 1 https://doi.org/10.1146/annurev-biophys-083012-130348	journal	May 2013
A uniqueness theorem for fluid pair correlation functions Henderson, R. L. Physics Letters A, Vol. 49, Issue 3 https://doi.org/10.1016/0375-9601(74)90847-0	journal	September 1974
High-Order Collocation Methods for Differential Equations with Random Inputs Xiu, Dongbin; Hesthaven, Jan S. SIAM Journal on Scientific Computing, Vol. 27, Issue 3 https://doi.org/10.1137/040615201	journal	January 2005
Effective potentials for representing polymers in melts as chains of interacting soft particles Clark, A. J.; McCarty, J.; Guenza, M. G. The Journal of Chemical Physics, Vol. 139, Issue 12 https://doi.org/10.1063/1.4821818	journal	September 2013
Direct construction of mesoscopic models from microscopic simulations Lei, Huan; Caswell, Bruce; Karniadakis, George Em Physical Review E, Vol. 81, Issue 2 https://doi.org/10.1103/PhysRevE.81.026704	journal	February 2010
Coarse-Graining in Polymer Simulation: From the Atomistic to the Mesoscopic Scale and Back Müller-Plathe, Florian ChemPhysChem, Vol. 3, Issue 9 https://doi.org/10.1002/1439-7641(20020916)3:9<754::AID-CPHC754>3.0.CO;2-U	journal	September 2002
Static and dynamic properties of dissipative particle dynamics Marsh, C. A.; Backx, G.; Ernst, M. H. Physical Review E, Vol. 56, Issue 2 https://doi.org/10.1103/PhysRevE.56.1676	journal	August 1997
Direct Molecular Dynamics Simulation of Branch Point Motion in Asymmetric Star Polymer Melts Zhou, Qiang; Larson, Ronald G. Macromolecules, Vol. 40, Issue 9 https://doi.org/10.1021/ma070072b	journal	May 2007
Versatile Object-Oriented Toolkit for Coarse-Graining Applications Rühle, Victor; Junghans, Christoph; Lukyanov, Alexander Journal of Chemical Theory and Computation, Vol. 5, Issue 12 https://doi.org/10.1021/ct900369w	journal	November 2009
Obtaining fully dynamic coarse-grained models from MD Español, Pep; Zúñiga, Ignacio Physical Chemistry Chemical Physics, Vol. 13, Issue 22 https://doi.org/10.1039/c0cp02826f	journal	January 2011
The fluctuation-dissipation theorem Kubo, R. Reports on Progress in Physics, Vol. 29, Issue 1 https://doi.org/10.1088/0034-4885/29/1/306	journal	January 1966
Transport dissipative particle dynamics model for mesoscopic advection-diffusion-reaction problems Li, Zhen; Yazdani, Alireza; Tartakovsky, Alexandre The Journal of Chemical Physics, Vol. 143, Issue 1 https://doi.org/10.1063/1.4923254	journal	July 2015
Dynamics of entangled linear polymer melts: A molecular‐dynamics simulation Kremer, Kurt; Grest, Gary S. The Journal of Chemical Physics, Vol. 92, Issue 8 https://doi.org/10.1063/1.458541	journal	April 1990
Probing red blood cell mechanics, rheology and dynamics with a two-component multi-scale model Li, Xuejin; Peng, Zhangli; Lei, Huan Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 372, Issue 2021 https://doi.org/10.1098/rsta.2013.0389	journal	August 2014
Mesoscale modeling of phase transition dynamics of thermoresponsive polymers Li, Zhen; Tang, Yu-Hang; Li, Xuejin Chemical Communications, Vol. 51, Issue 55 https://doi.org/10.1039/C5CC01684C	journal	January 2015
Statistical Mechanics of Dissipative Particle Dynamics Español, P.; Warren, P. Europhysics Letters (EPL), Vol. 30, Issue 4 https://doi.org/10.1209/0295-5075/30/4/001	journal	May 1995
Calculation of effective interaction potentials from radial distribution functions: A reverse Monte Carlo approach Lyubartsev, Alexander P.; Laaksonen, Aatto Physical Review E, Vol. 52, Issue 4 https://doi.org/10.1103/PhysRevE.52.3730	journal	October 1995
Interatomic Potentials from First-Principles Calculations: The Force-Matching Method Ercolessi, F.; Adams, J. B. Europhysics Letters (EPL), Vol. 26, Issue 8 https://doi.org/10.1209/0295-5075/26/8/005	journal	June 1994
Equation of motion for coarse-grained simulation based on microscopic description Kinjo, Tomoyuki; Hyodo, Shi-aki Physical Review E, Vol. 75, Issue 5 https://doi.org/10.1103/PhysRevE.75.051109	journal	May 2007
A Multiscale Coarse-Graining Method for Biomolecular Systems Izvekov, Sergei; Voth, Gregory A. The Journal of Physical Chemistry B, Vol. 109, Issue 7 https://doi.org/10.1021/jp044629q	journal	February 2005
The power of coarse graining in biomolecular simulations: The power of coarse graining in biomolecular simulations Ingólfsson, Helgi I.; Lopez, Cesar A.; Uusitalo, Jaakko J. Wiley Interdisciplinary Reviews: Computational Molecular Science, Vol. 4, Issue 3 https://doi.org/10.1002/wcms.1169	journal	August 2013
Effective Interaction between Star Polymers Jusufi, A.; Watzlawek, M.; Löwen, H. Macromolecules, Vol. 32, Issue 13 https://doi.org/10.1021/ma981844u	journal	June 1999
The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations Xiu, Dongbin; Karniadakis, George Em SIAM Journal on Scientific Computing, Vol. 24, Issue 2 https://doi.org/10.1137/S1064827501387826	journal	January 2002
Simulating flow of DNA suspension using dissipative particle dynamics Fan, Xijun; Phan-Thien, Nhan; Chen, Shuo Physics of Fluids, Vol. 18, Issue 6 https://doi.org/10.1063/1.2206595	journal	January 2006
Uncertainty Quantification in MD Simulations. Part II: Bayesian Inference of Force-Field Parameters Rizzi, F.; Najm, H. N.; Debusschere, B. J. Multiscale Modeling & Simulation, Vol. 10, Issue 4 https://doi.org/10.1137/110853170	journal	January 2012
Mesoscale modeling: solving complex flows in biology and biotechnology Mills, Zachary Grant; Mao, Wenbin; Alexeev, Alexander Trends in Biotechnology, Vol. 31, Issue 7 https://doi.org/10.1016/j.tibtech.2013.05.001	journal	July 2013
The multiscale coarse-graining method. II. Numerical implementation for coarse-grained molecular models Noid, W. G.; Liu, Pu; Wang, Yanting The Journal of Chemical Physics, Vol. 128, Issue 24 https://doi.org/10.1063/1.2938857	journal	June 2008
Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism Li, Zhen; Bian, Xin; Li, Xiantao The Journal of Chemical Physics, Vol. 143, Issue 24 https://doi.org/10.1063/1.4935490	journal	December 2015
Reweighted minimization method for stochastic elliptic differential equations Yang, Xiu; Karniadakis, George Em Journal of Computational Physics, Vol. 248 https://doi.org/10.1016/j.jcp.2013.04.004	journal	September 2013
Perspective: Coarse-grained models for biomolecular systems Noid, W. G. The Journal of Chemical Physics, Vol. 139, Issue 9 https://doi.org/10.1063/1.4818908	journal	September 2013
The relative entropy is fundamental to multiscale and inverse thermodynamic problems Shell, M. Scott The Journal of Chemical Physics, Vol. 129, Issue 14 https://doi.org/10.1063/1.2992060	journal	October 2008
Simultaneous Iterative Boltzmann Inversion for Coarse-Graining of Polyurea Agrawal, Vipin; Arya, Gaurav; Oswald, Jay Macromolecules, Vol. 47, Issue 10 https://doi.org/10.1021/ma500320n	journal	May 2014
Enhancing sparsity of Hermite polynomial expansions by iterative rotations Yang, Xiu; Lei, Huan; Baker, Nathan A. Journal of Computational Physics, Vol. 307 https://doi.org/10.1016/j.jcp.2015.11.038	journal	February 2016
Deriving effective mesoscale potentials from atomistic simulations: Mesoscale Potentials from Atomistic Simulations Reith, Dirk; Pütz, Mathias; Müller-Plathe, Florian Journal of Computational Chemistry, Vol. 24, Issue 13 https://doi.org/10.1002/jcc.10307	journal	August 2003
Statistical-Mechanical Theory of Irreversible Processes. I. General Theory and Simple Applications to Magnetic and Conduction Problems Kubo, Ryogo Journal of the Physical Society of Japan, Vol. 12, Issue 6 https://doi.org/10.1143/JPSJ.12.570	journal	June 1957
No-go theorem in many-body dissipative particle dynamics Warren, Patrick B. Physical Review E, Vol. 87, Issue 4 https://doi.org/10.1103/PhysRevE.87.045303	journal	April 2013
Comparative atomistic and coarse-grained study of water: What do we lose by coarse-graining? Wang, Han; Junghans, Christoph; Kremer, Kurt The European Physical Journal E, Vol. 28, Issue 2 https://doi.org/10.1140/epje/i2008-10413-5	journal	January 2009
The multiscale coarse-graining method. I. A rigorous bridge between atomistic and coarse-grained models Noid, W. G.; Chu, Jhih-Wei; Ayton, Gary S. The Journal of Chemical Physics, Vol. 128, Issue 24 https://doi.org/10.1063/1.2938860	journal	June 2008
Enhancing Sparsity of Hermite Polynomial Expansions by Iterative Rotations Yang, Xiu; Lei, Huan; Baker, Nathan A. arXiv https://doi.org/10.48550/arxiv.1506.04344	text	January 2015
Vapour-liquid coexistence in many-body dissipative particle dynamics Warren, P. B. arXiv https://doi.org/10.48550/arxiv.cond-mat/0306027	text	January 2003
Interatomic potentials from first-principles calculations: the force-matching method Ercolessi, Furio; Adams, James B. arXiv https://doi.org/10.48550/arxiv.cond-mat/9306054	text	January 1993

Cited By (11)

Toward High Fidelity Materials Property Prediction from Multiscale Modeling and Simulation Vassaux, Maxime; Sinclair, Robert C.; Richardson, Robin A. Advanced Theory and Simulations, Vol. 3, Issue 1 https://doi.org/10.1002/adts.201900122	journal	October 2019
Force‐field parametrization based on radial and energy distribution functions Chiba, Shuntaro; Okuno, Yasushi; Honma, Teruki Journal of Computational Chemistry, Vol. 40, Issue 29 https://doi.org/10.1002/jcc.26035	journal	July 2019
A note on hydrodynamics from dissipative particle dynamics Bian, X.; Li, Z.; Adams, N. A. Applied Mathematics and Mechanics, Vol. 39, Issue 1 https://doi.org/10.1007/s10483-018-2257-9	journal	December 2017
Implicit-solvent coarse-grained modeling for polymer solutions via Mori-Zwanzig formalism Wang, Shu; Li, Zhen; Pan, Wenxiao Soft Matter, Vol. 15, Issue 38 https://doi.org/10.1039/c9sm01211g	journal	January 2019
Multi-scale modeling of the polymer–filler interaction Kempfer, Kevin; Devémy, Julien; Dequidt, Alain Soft Matter, Vol. 16, Issue 6 https://doi.org/10.1039/c9sm01959f	journal	January 2020
Computing the non-Markovian coarse-grained interactions derived from the Mori–Zwanzig formalism in molecular systems: Application to polymer melts Li, Zhen; Lee, Hee Sun; Darve, Eric The Journal of Chemical Physics, Vol. 146, Issue 1 https://doi.org/10.1063/1.4973347	journal	January 2017
Nature of intrinsic uncertainties in equilibrium molecular dynamics estimation of shear viscosity for simple and complex fluids Kim, Kang-Sahn; Han, Myung Hoon; Kim, Changho The Journal of Chemical Physics, Vol. 149, Issue 4 https://doi.org/10.1063/1.5035119	journal	July 2018
Development of a coarse-grain model for the description of the metal oxide-polymer interface from a bottom-up approach Solano Canchaya, José G.; Dequidt, Alain; Garruchet, Sebastien The Journal of Chemical Physics, Vol. 151, Issue 6 https://doi.org/10.1063/1.5115148	journal	August 2019
Static structure of sodium polystyrene sulfonate solutions obtained through a coarse-grained model Jacinto-Méndez, Damián; Villada-Balbuena, Mario; Cruz y. Cruz, Sara G. Molecular Physics, Vol. 116, Issue 17 https://doi.org/10.1080/00268976.2018.1471225	journal	May 2018
Force-sampling methods for density distributions as instances of mapped averaging Purohit, Apoorva; Schultz, Andrew J.; Kofke, David A. Molecular Physics, Vol. 117, Issue 20 https://doi.org/10.1080/00268976.2019.1572243	journal	January 2019
Nature of Intrinsic Uncertainties in Equilibrium Molecular Dynamics Estimation of Shear Viscosity for Simple and Complex Fluids Kim, Kang-Sahn; Han, Myung Hoon; Kim, Changho arXiv https://doi.org/10.48550/arxiv.1807.08063	text	January 2018

Similar Records

A comparative study of coarse-graining methods for polymeric fluids: Mori-Zwanzig vs. iterative Boltzmann inversion vs. stochastic parametric optimization

Journal Article · Thu Jul 28 00:00:00 EDT 2016 · Journal of Chemical Physics · OSTI ID:1356514

Li, Zhen; Bian, Xin; Yang, Xiu

Computing the non-Markovian coarse-grained interactions derived from the Mori–Zwanzig formalism in molecular systems: Application to polymer melts

Journal Article · Wed Jan 04 00:00:00 EST 2017 · Journal of Chemical Physics · OSTI ID:1356514

Li, Zhen; Lee, Hee Sun; Darve, Eric; +1 more

Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism

Journal Article · Mon Dec 28 00:00:00 EST 2015 · Journal of Chemical Physics · OSTI ID:1356514

Li, Zhen; Bian, Xin; Li, Xiantao

Related Subjects

97 MATHEMATICS AND COMPUTING
Molecular dynamics
Polymers
Stochastic processes
Gyration radius
Many body problems
Newtonian mechanics
Nonequilibrium statistical mechanics
Static properties
Thermodynamic properties
Classical statistical mechanics

Title: A comparative study of coarse-graining methods for polymeric fluids: Mori-Zwanzig vs. iterative Boltzmann inversion vs. stochastic parametric optimization

Citation Formats

References (51)

Cited By (11)

Similar Records

Related Subjects