Sultan, Saad Raheem
(2013)
Modeling And Optimization Of Styrene Syndiotactic Polymerization Through Multiscale.
PhD thesis, Universiti Sains Malaysia.
Abstract
The integration of modeling, simulation and optimization provides powerful
tools for supporting advanced decision making in the competitive market. However,
when applying the tools to polymerization processing, the challenging task is to
accommodate the predictability of the mathematical model and the capability of
model-based optimization due to its inherent complexities. In the present study, three
model approaches are proposed, i.e. a data based model, a kinetic model and a
multiscale model, whereby the developed models are implemented into the
syndiotactic polymerization of styrene. The data based model was developed based
on the correlation model from experimentally obtained data, where the classical
linear or nonlinear models can be applied to correlate the variation in any set of data
using experimental design. The kinetic model includes the polymerization kinetics
scheme, polymerization rate analysis and polymer molecular weight distribution. The
multiscale model is an integrated framework which consists of the coupling between
the single particle growth model at mesoscale and the mixing phenomenon model at
macroscale with the kinetic model at microscale, where by both particle growth and
mixing phenomenon are considered to control the mass transfer limitations in the
syndiotactic polymerization of styrene. To verify these models and to evaluate all
model parameters, syndiotactic polymerization of styrene over a silica supported
metallocene catalyst was performed. Two metallocene supported catalysts were
synthesized for styrene polymerization, the titanium mono cyclopentadienyl and
Indenyl complexes. It was found that the Indenyl complex possessed high catalytic
activity with selective syndiotacticity behavior.
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