Premium
Monte Carlo Simulation of Randomly Branched Step‐Growth Polymers: Generation and Analysis of Representative Molecular Ensembles
Author(s) -
Hillegers L. Tom,
Kapnistos Michael,
Nijenhuis Atze,
Slot Johan J. M.,
Steeman Paul A. M.
Publication year - 2011
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.201000071
Subject(s) - monte carlo method , statistical physics , recipe , polymer , set (abstract data type) , molecule , computational chemistry , chemistry , computer science , mathematics , physics , organic chemistry , statistics , food science , programming language
A Monte Carlo simulation procedure has been set up and applied to generate representative ensembles of randomly branched step‐growth polymers based on their reaction recipe. The molecular distributions thus obtained are consistent with those from statistical/analytical approaches. However, because the current method gives access to the complete ensemble of simulated molecules, a very detailed structural analysis is possible. Our procedures are applicable to any ‘A f B g ’ system with f + g ≥ 1. We apply this approach to randomly branched polyamides in order to gain insight into their molecular structure and understand the effect of the reaction recipe on the final product.