Macromolecules · 1999 · 286 citations · 42 references
Natural SciencesChemistryMaterials ScienceComputational Materials ScienceComputational ThermodynamicsPolymer ChemistryCondensed Matter SimulationsMolecular SimulationPolymer ConformationPolymer PhysicsPolymer SimulationPolymer ThermodynamicsAtomistic Polymer ModelingChain ConformationChain Length DistributionFinite-size EffectsMolecular Conformation In MeltsMonte Carlo Simulation Of PolymersPolydispersity Index AnalysisPolymer Conformation In Melts
The recently introduced end-bridging (EB) Monte Carlo move is revisited, and a thorough analysis of its geometric formulation and numerical implementation is given. Detailed results are presented from applying the move, along with concerted rotation, in atomistic simulations of polyethylene (PE) melt systems with mean molecular lengths ranging from C 78 up to C 500, flat molecular weight distributions, and polydispersity indices I ranging from 1.02 to 1.12. To avoid finite system-size effects, most simulations are executed in a superbox containing up to 5000 mers and special neighbor list strategies are implemented. For all chain lengths considered, excellent equilibration is observed of the thermodynamic and conformational properties of the melt at all length scales, from the level of the bond length to the level of the chain end-to-end vector. In sharp contrast, if no end bridging is allowed among the Monte Carlo moves, no equilibration is achieved, even for the C 78 system. The polydispersity index I is found to have no effect on the equilibrium properties of the melt. To quantify the efficiency of the EB Monte Carlo move, the CPU time t 0 required for the chain center of mass to travel a distance equal to the root-mean-square end-to-end distance is estimated by simple analytical arguments. It is found that t 0 should scale as n /( X̄ Δ 2.5 ), where n is the total number of mers in the system, X̄ is the average chain length, and Δ ≃ [3( I − 1)] 1/2 is the reduced width of the chain-length distribution function. This means that, if the size of the model system and the shape of the chain-length distribution are kept constant, systems of larger average molecular weight equilibrate faster, a remarkable attribute of the EB Monte Carlo method. The simulation results obey the estimated scaling of t 0 with X̄, n, and Δ remarkably well in the range of chain lengths and polydispersities for which the premises of the analysis are not violated (mean chain lengths greater than C 156 and polydispersity indices above about 1.07). Results for volumetric behavior, structure, and chain conformation at temperature T = 450 K and pressure P ranging from 1 to 800 atm are presented, using three different PE united atom models proposed in the recent literature. All three models are shown to overestimate the density by ca. 4% and also overestimate the stiffness of chains. The Yoon et al. model is in best agreement with experimental characteristic ratios. Simulation predictions for the structure factor and for the chain-length dependence of the density are in excellent agreement with experiment.
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Principles of Polymer Chemistry.
Maurice L. Huggins · Journal of the American Chemical Society · 1954 · 16.6K citations
Computer Simulation of Liquids
S. P, K. J · Journal of Molecular Liquids · 1988 · 15.9K citations
The Theory of Polymer Dynamics
G. Marrucci · Journal of Non-Newtonian Fluid Mechanics · 1987 · 9.8K citations
Statistical mechanics of chain molecules
Paul J. Flory, M.V. Volkenstein · Biopolymers · 1969 · 6.5K citations
Natural Sciences, Chemistry, Physics +14