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On the use of the gaussian chain as a monte carlo simulation model for the equilibrium properties of polymer solutions
Author(s) -
Jorge Sonia,
Freire Juan J.,
Rey Antonio
Publication year - 1997
Publication title -
macromolecular theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 56
eISSN - 1521-3919
pISSN - 1022-1344
DOI - 10.1002/mats.1997.040060117
Subject(s) - gaussian , monte carlo method , statistical physics , gaussian network model , distortion (music) , excluded volume , function (biology) , distribution (mathematics) , physics , mathematics , chemistry , polymer , computational chemistry , statistics , mathematical analysis , nuclear magnetic resonance , amplifier , optoelectronics , cmos , evolutionary biology , biology
We have explored the performance of a simulation model for Gaussian chains at different concentrations in a good solvent. The Gaussian statistics for the distances between contiguous beads in the model is directly implemented in the individual moves of a Monte Carlo algorithm. When the results of conformational properties for the Gaussian model are compared with those provided by a freely jointed model in the same conditions, significant differences arise at finite concentrations. The modeled Gaussian chain yields incorrect results for the quadratic average dimensions 〈 R 2 〉 and 〈 S 2 〉 at high concentrations, but correctly reproduces the results for the scaled end‐to‐end distance distribution function at any concentration, showing the effects of the screening of excluded volume when concentration increases. The reason for the wrong behavior of the simulated Gaussian model comes from a strong distortion of the “bond distance” distribution as a result of the concentration increase. We conclude that this model can only be safely applied to infinitely dilute solutions.