Mathematical Modeling of ARGET Copolymerization of Styrene and Acrylonitrile. II: Efficient Calculation of Bivariate Distributions using Parallel Computing

PINTOS, ESTEBAN; FORTUNATTI, CECILIA; BRANDOLIN, ADRIANA; SARMORIA, CLAUDIA; ASTEASUAIN, MARIANO

Bahía Blanca

Congreso; International Conference of Production Research Americas 2020 (ICPR-Americas 2020); 2020

Comité organizador

The probability generating function (pgf) technique in combination with parallel computing is a very valuable tool for modelling bivariate distributions in polymerization systems. Models with this level of detail usually involve a very large system of stiff differential equations which demand efficient solution techniques. Part I of this work presented the parameter estimation of a mathematical model of the Activators ReGenerated by Electron Transfer ? Atom Transfer Radical Polymerization (ARGET-ATRP) of styrene and acrylonitrile (SAN). A good agreement between model and experimental data was achieved. Part II focuses on the modeling of the bivariate molecular weight distribution (MWD)-copolymer composition distribution (CCD) of the copolymer, as well as the overall MWD and CCDs. Julia, an open-source language specifically designed for scientific computing, was used to implement the mathematical model. The parallelized implementation of the code in Julia allowed to compute the bivariate distributions in relatively short times.