PROBABILISTIC MULTISITE MODELING OF PROPENE POLYMERIZATION USING MARKOV-MODELS

Possible propagation mechanisms in propene polymerization using hetero geneous catalysts are described by combinations of Bernoulli and first - or even second-order Markov models. Both NMR-measured pentad fractio ns and GPC(a))-measured molecular weight distributions are directly ta ken into account to fit an appropriate propagation model for a specifi c catalyst. The analytical data so obtained have been used for an exam ination of the applicability of multi-site propagation models and for estimation of the main parameters in each model. The propagation and t ermination probabilities are estimated, as are ''mix'' parameters givi ng the fraction of the polymer population stemming from each kind of p ropagation mechanism. In this way the subpopulation produced by each s ite is characterized in terms of tacticity and molecular weight distri bution. A three-site model is required to explain the measured data pr operly.