Abstract
Evaluation of effective coarse graining (CG) degree and reasonable speedup relative to all-atomistic (AA) model was conducted to provide a basis for building appropriate larger-scale model. The reproducibility of atomistic conformation and temperature transferability both act as the analysis criteria to resolve the maximum acceptable CG degree. Taking short- and long time spans into account simultaneously in the estimation of computational speedup, a dynamic scaling factor is accessible in fitting mean squared displacement ratio of CG to AA as an exponential function. Computing loss in parallel running is an indispensable component in acceleration, which was also added in the evaluation. Subsequently, a quantified prediction of CG speedup arises as a multiplication of dynamic scaling factor, computing loss, time step, and the square of reduction in the number of degrees of freedom. Polyethylene oxide was adopted as a reference system to execute the direct Boltzmann inversion and iterative Boltzmann inversion. Bonded and non-bonded potentials were calculated in CG models with 1~4 monomers per bead. The effective CG degree was determined as two at the most with a speedup of four orders magnitude over AA in this study. Determination of effectiveness CG degree and the corresponding speedup prediction provide available tools in larger spatiotemporal-scale calculations.
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Gooneie A, Schuschnigg S, Holzer C (2017) A review of multiscale computational methods in polymeric materials. Polymers 9(1):1–80. https://doi.org/10.3390/polym9010016
Ohkuma T, Kremer K (2017) Comparison of two coarse-grained models of cis-polyisoprene with and without pressure correction. Polymer 130:88–101. https://doi.org/10.1016/j.polymer.2017.09.062
Noid WG (2013) Systematic methods for structurally consistent coarse-grained models. In: Monticelli L, Salonen E (eds) Biomolecular Simulations: Methods and Protocols. Humana Press, Totowa, pp 487–531. https://doi.org/10.1007/978-1-62703-017-5_19
Empereur-mot C, Pesce L, Bochicchio D, Perego C, Pavan GM (2020) Swarm-CG: Automatic parametrization of bonded terms in coarse-grained models of simple to complex molecules via fuzzy self-tuning particle swarm optimization. ChemRxiv. https://doi.org/10.26434/chemrxiv.12613427.v2
Bejagam KK, Singh S, An Y, Deshmukh SA (2018) Machine-learned coarse-grained models. J Phys Chem Lett 9(16):4667–4672. https://doi.org/10.1021/acs.jpclett.8b01416
Reith D, Putz M, Muller-Plathe F (2003) Deriving effective mesoscale potentials from atomistic simulations. J Comput Chem 24(13):1624–1636. https://doi.org/10.1002/jcc.10307
Sovova Z, Berka K, Otyepka M, Jurecka P (2015) Coarse-grain simulations of skin ceramide NS with newly derived parameters clarify structure of melted phase. J Phys Chem B 119(10):3988–3998. https://doi.org/10.1021/jp5092366
Schulze E, Stein M (2018) Simulation of mixed self-assembled monolayers on gold: effect of terminal alkyl anchor chain and monolayer composition. J Phys Chem B 122(31):7699–7710. https://doi.org/10.1021/acs.jpcb.8b05075
Li Y, Kroger M, Liu WK (2011) Primitive chain network study on uncrosslinked and crosslinked cis-polyisoprene polymers. Polymer 52(25):5867–5878. https://doi.org/10.1016/j.polymer.2011.10.044
Li Y, Tang S, Abberton BC, Kroger M, Burkhart C, Jiang B, Papakonstantopoulos GJ, Poldneff M, Liu WK (2012) A predictive multiscale computational framework for viscoelastic properties of linear polymers. Polymer 53(25):5935–5952. https://doi.org/10.1016/j.polymer.2012.09.055
Li X, Kou D, Rao S, Liang H (2006) Developing a coarse-grained force field for the diblock copolymer poly (styrene-b-butadiene) from atomistic simulation. J Chem Phys 124(20):204909. https://doi.org/10.1063/1.2200694
Tschop W, Kremer K, Batoulis J, Burger T, Hahn O (1998) Simulation of polymer melts. I. Coarse-graining procedure for polycarbonates. Acta Polym 49(2-3):61–74. https://doi.org/10.1002/(sici)1521-4044(199802)49:2/3<61::aid-apol61>3.0.co;2-v
Agrawal V, Peralta P, Li YY, Oswald J (2016) A pressure-transferable coarse-grained potential for modeling the shock Hugoniot of polyethylene. J Chem Phys 145(10). https://doi.org/10.1063/1.4962255
Moore TC, Iacovella CR, McCabe C (2014) Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion. J Chem Phys 140(22). https://doi.org/10.1063/1.4880555
Müller M, JJd P (2013) Computational approaches for the dynamics of structure formation in self-assembling polymeric materials. Annu Rev Mater Res 43(1):1–34. https://doi.org/10.1146/annurev-matsci-071312-121618
Salerno KM, Agrawal A, Perahia D, Grest GS (2016) Resolving dynamic properties of polymers through coarse-grained computational studies. Phys Rev Lett 116(5). https://doi.org/10.1103/PhysRevLett.116.058302
Salerno KM, Agrawal A, Peters BL, Perahia D, Grest GS (2016) Dynamics in entangled polyethylene melts. Eur Phys J-Spec Top 225(8-9):1707–1722. https://doi.org/10.1140/epjst/e2016-60142-7
Depa P, Chen CX, Maranas JK (2011) Why are coarse-grained force fields too fast? A look at dynamics of four coarse-grained polymers. J Chem Phys 134(1). https://doi.org/10.1063/1.3513365
Depa PK, Maranas JK (2005) Speed up of dynamic observables in coarse-grained molecular-dynamics simulations of unentangled polymers. J Chem Phys 123(9):94901. https://doi.org/10.1063/1.1997150
Lee H, de Vries AH, Marrink S-J, Pastor RW (2009) A coarse-grained model for polyethylene oxide and polyethylene glycol: conformation and hydrodynamics. J Phys Chem B 113(40):13186–13194. https://doi.org/10.1021/jp9058966
Nawaz S, Carbone P (2014) Coarse-Graining Poly (ethylene oxide)–Poly (propylene oxide)–Poly(ethylene oxide) (PEO–PPO–PEO) Block copolymers using the MARTINI force field. J Phys Chem B 118(6):1648–1659. https://doi.org/10.1021/jp4092249
Wu C (2019) Bulk modulus of poly(ethylene oxide) simulated using the systematically coarse-grained model. Comput Mater Sci 156:89–95. https://doi.org/10.1016/j.commatsci.2018.09.043
Brini E, Algaer EA, Ganguly P, Li C, Rodriguez-Ropero F, van der Vegt NFA (2013) Systematic coarse-graining methods for soft matter simulations - a review. Soft Matter 9(7):2108–2119. https://doi.org/10.1039/C2SM27201F
Lee H, Venable RM, MacKerell AD, Pastor RW (2008) Molecular dynamics studies of polyethylene oxide and polyethylene glycol: hydrodynamic radius and shape anisotropy. Biophys J 95(4):1590–1599. https://doi.org/10.1529/biophysj.108.133025
Martínez L, Andrade R, Birgin EG, Martínez JM (2009) PACKMOL: a package for building initial configurations for molecular dynamics simulations. J Comput Chem 30(13):2157–2164. https://doi.org/10.1002/jcc.21224
Agrawal V, Arya G, Oswald J (2014) Simultaneous iterative Boltzmann inversion for coarse-graining of polyurea. Macromolecules 47(10):3378–3389. https://doi.org/10.1021/ma500320n
Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J Comput Phys 117:1–19
Ruhle V, Junghans C, Lukyanov A, Kremer K, Andrienko D (2009) Versatile object-oriented toolkit for coarse-graining applications. J Chem Theory Comput 5(12):3211–3223. https://doi.org/10.1021/ct900369w
Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph Model 14(1):33–38
Alexander S (2010) Visualization and analysis of atomistic simulation data with OVITO–the open visualization tool. Model Simul Mater Sc 18(1):015012. https://doi.org/10.1088/0965-0393/18/1/015012
van Zon A, Mos B, Verkerk P, de Leeuw SW (2001) On the dynamics of PEO-NaI polymer electrolytes. Electrochim Acta 46(10):1717–1721. https://doi.org/10.1016/S0013-4686(00)00776-3
Wang QF, Keffer DJ, Nicholson DM (2011) A coarse-grained model for polyethylene glycol polymer. J Chem Phys 135(21). https://doi.org/10.1063/1.3664623
Choi E, Mondal J, Yethiraj A (2014) Coarse-grained models for aqueous polyethylene glycol solutions. J Phys Chem B 118(1):323–329. https://doi.org/10.1021/jp408392b
Taddese T, Carbone P (2017) Effect of chain length on the partition properties of (polyethylene oxide): comparison between MARTINI coarse-grained and atomistic models. J Phys Chem B 121(7):1601–1609. https://doi.org/10.1021/acs.jpcb.6b10858
Wu C (2018) Multiscale modeling scheme for simulating polymeric melts: application to poly(ethylene oxide). Macromol Theory Simul 27(1). https://doi.org/10.1002/mats.201700066
Chen CX, Depa P, Sakai VG, Maranas JK, Lynn JW, Peral I, Copley JRD (2006) A comparison of united atom, explicit atom, and coarse-grained simulation models for poly(ethylene oxide). J Chem Phys 124(23):234901. https://doi.org/10.1063/1.2204035
Cordeiro RM, Zschunke F, Mueller-Plathe F (2010) Mesoscale molecular dynamics simulations of the force between surfaces with grafted poly(ethylene oxide) chains derived from atomistic simulations. Macromolecules 43(3):1583–1591. https://doi.org/10.1021/ma902060k
Fischer J, Paschek D, Geiger A, Sadowski G (2008) Modeling of aqueous poly(oxyethylene) solutions: 1. Atomistic Simulations. J Phys Chem B 112(8):2388–2398. https://doi.org/10.1021/jp0765345
Chen QP, Xie S, Foudazi R, Lodge TP, Siepmann JI (2018) Understanding the molecular weight dependence of χ and the effect of dispersity on polymer blend phase diagrams. Macromolecules 51(10):3774–3787. https://doi.org/10.1021/acs.macromol.8b00604
Stubbs JM, Potoff JJ, Siepmann JI (2004) Transferable potentials for phase equilibria. 6. United-Atom Description for Ethers, Glycols, Ketones, and Aldehydes. J Phys Chem B 108(45):17596–17605. https://doi.org/10.1021/jp049459w
Glotzer SC, Paul W (2002) Molecular and mesoscale simulation methods for polymer materials. Annu Rev Mater Res 32:401–436. https://doi.org/10.1146/annurev.matsci.32.010802.112213
Bayramoglu B, Faller R (2013) Modeling of polystyrene under confinement: exploring the limits of iterative Boltzmann inversion. Macromolecules 46(19):7957–7976. https://doi.org/10.1021/ma400831g
Huang H, Wu L, Xiong H, Sun H (2019) A transferrable coarse-grained force field for simulations of polyethers and polyether blends. Macromolecules 52(1):249–261. https://doi.org/10.1021/acs.macromol.8b01802
Xie ZM, Chai DL, Wang YS, Tan HF (2016) Directly modifying the nonbonded potential based on the standard iterative boltzmann inversion method for coarse-grained force fields. J Phys Chem B 120(45):11834–11844. https://doi.org/10.1021/acs.jpcb.6b06457
Enns JB, Simha R (2006) Transitions in semicrystalline polymers. II. Polyoxymethylene and poly(ethylene oxide). J Macromol Sci B 13(1):25–47. https://doi.org/10.1080/00222347708208751
Iwaoka N, Hagita K, Takano H (2018) Multipoint segmental repulsive potential for entangled polymer simulations with dissipative particle dynamics. J Chem Phys 149:114901. https://doi.org/10.1063/1.5046755
Sirk TW, Slizoberg YR, Brennan JK, Lisal M, Andzelm JW (2012) An enhanced entangled polymer model for dissipative particle dynamics. J Chem Phys 136(13):134903. https://doi.org/10.1063/1.3698476
Niedzwiedz K, Wischnewski A, Pyckhout-Hintzen W, Allgaier J, Richter D, Faraone A (2008) Chain dynamics and viscoelastic properties of poly(ethylene oxide). Macromolecules 41:4866–4872. https://doi.org/10.1021/ma800446n
Peters BL, Salerno KM, Agrawal A, Perahia D, Grest GS (2017) Coarse grained modeling of polyethylene melts: effect on dynamics. J Chem Theory Comput 13(6):2890–2896. https://doi.org/10.1021/acs.jctc.7b00241
Acknowledgments
The parallel computing was supported by the National Supercomputing Center in Shenzhen (Shenzhen Cloud Computing Center) and the Computing Facility, Institute of Mechanics, Chinese Academy of Sciences.
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This study was funded by the National Natural Science Foundation of China (Project No. 11672314).
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Conceptualization: Lijuan Liao; Methodology: Lijuan Liao and Changyu Meng; Formal analysis and investigation: Lijuan Liao and Changyu Meng; Writing—original draft preparation: Lijuan Liao; Funding acquisition: Lijuan Liao; Supervision: Chenguang Huang.
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Liao, L., Meng, C. & Huang, C. Effectiveness of coarse graining degree and speedup on the dynamic properties of homopolymer. J Mol Model 27, 55 (2021). https://doi.org/10.1007/s00894-020-04661-5
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DOI: https://doi.org/10.1007/s00894-020-04661-5