info:eu-repo/semantics/article
Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions
Fecha
2017-08Registro en:
Fortunatti, Cecilia; Sarmoria, Claudia; Brandolin, Adriana; Asteasuain, Mariano; Modeling of the bivariate molecular weight distribution-copolymer composition distribution in RAFT copolymerization using probability generating functions; Elsevier Science; Computational Materials Science; 136; 8-2017; 280-296
0927-0256
CONICET Digital
CONICET
Autor
Fortunatti, Cecilia
Sarmoria, Claudia
Brandolin, Adriana
Asteasuain, Mariano
Resumen
In this work, we develop a mathematical model of a RAFT copolymerization process able to predict average molecular properties as well as the full bivariate molecular weight distribution – copolymer composition distribution (MWD-CCD) of the copolymer. This model takes into account the three main kinetic theories proposed in the literature. The bivariate MWD-CCD is obtained by means of the 2D probability generating function (pgf) technique. This modeling technique can be used without any simplifying assumptions or a priori knowledge of the distribution shape. The results highlight the advantages of simulation as a powerful tool to get insight in the relationship between operating conditions and molecular structure.