Modeling of RAFT Polymerization using Probability Generating Functions. Detailed Prediction of Full Molecular Weight Distributions and Sensitivity Analysis
作者： Cecilia Fortunatti , Claudia Sarmoria , Adriana Brandolin , Mariano Asteasuain
关键词: Biological system 、 Organic chemistry 、 Population 、 Raft 、 Polymerization 、 Sensitivity (control systems) 、 Reversible addition−fragmentation chain-transfer polymerization 、 Direct integration of a beam 、 Joint probability distribution 、 Probability-generating function 、 Chemistry
摘要: A mathematical model of RAFT polymerization processes is presented capable predicting the full molecular weight distribution (MWD) through use probability generating functions (pgf). The bivariate intermediate species calculated. able to work with three kinetic mechanisms currently under discussion for explaining observed behavior this type polymerization. For comparison purposes, population balances are also solved by direct integration resulting equations. results show that pgf technique allows obtaining accurate solutions very small computational times systems any average weight. Spurious oscillations in high tail MWD can be easily disregarded. sensitivity analysis over several constants performed, showing effects changing their values orders magnitude. This aims showcase enormous potential modeling and optimization complex kinetics.
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