arXiv (Cornell University) · 2002 · 37 citations · 0 references
Natural SciencesChemistryComputational ChemistryPhysical ChemistryPolymer ChemistryAtomistic ModelingAtomistic SimulationCoarse-grained ModelingInteratomic PotentialsMolecular SimulationPolymer SimulationAll-atom ModelingAll-atom SimulationsAtomistic Polymer ModelingCoarse-grained Polymer ModelsConcentrationForce Field ModelsPotential Field InversionPotential Of Mean Force
The study generalizes an iterative potential‑inversion method from simple liquids to polymer systems. The method iteratively refines effective potentials by comparing mean‑force potentials of guessed and true distributions, and is applied to a 13:1 coarse‑grained polyisoprene model in both solution and melt. The algorithm converges rapidly for all trial functions, but force fields derived for polyisoprene differ between solution and melt, showing a single force field cannot span concentration regimes.
We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liquid systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few iterations. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 reduction of the degrees of freedom. This procedure was performed for PI solutions as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concentration regimes.