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Simultaneous Deconvolution of MWD and CCD of Ethylene/1‐ O lefin Copolymers Using Genetic Algorithm
Author(s) -
Nanthapoolsub Uthane,
Anantawaraskul Siripon,
Saengkhamkhom Khomwat
Publication year - 2013
Publication title -
macromolecular symposia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 76
eISSN - 1521-3900
pISSN - 1022-1360
DOI - 10.1002/masy.201300035
Subject(s) - deconvolution , biological system , ethylene , copolymer , algorithm , genetic algorithm , heuristic , molar mass distribution , materials science , chemistry , computer science , polymer , mathematical optimization , catalysis , mathematics , organic chemistry , biology
Summary Multiple‐site‐type catalytic systems produce ethylene/1‐olefin copolymers with broad molecular weight distribution (MWD) and chemical composition distribution (CCD) because each active site type produces chains with distinct chain microstructures. Simultaneous deconvolution of the MWD and CCD can be used to identify the number of active site types and chain microstructures produced on each active site type by performing parameter estimation to minimize the sum of the squares of differences between experimental and model data. However, conventional optimization algorithms often rely on the adequate initial guess. In this work, a genetic algorithm, which is a stochastic optimization search heuristic that mimics the natural evolution process, was implemented during the simultaneous deconvolution. The proposed approach was validated with simulated data of model ethylene/1‐butene copolymers produced using a system with three active site types.