Statistical Propagation Models for Ziegler-Natta Polymerization

Abstract

Statistical probability models are widely used as a convenient theoretical framework for the characterization of polyolefins. Other than the commonly known enantiomorphic-site, Bemoullian, and Markovian models, many additional models have been devised in the last few years. This work surveys the various models proposed for the description of Ziegler-Natta polymerization. The models may involve propagations that are controlled by monomer units at the propagating chain ends or by the catalytic sites. The models may involve multiple active sites. They may involve an active site that switches back and forth between two states. Finally, the Markovian or enantiomorphic-site probabilities may be perturbed, leading to compositional heterogeneity. These models and the analytical methodologies involved are applied to published NMR data to test for the presence of dual catalytic-site/chain-end control and tacticity heterogeneity (distribution) in polypropylene made with Group IV metallocene catalysts, and to check for blocky microstructure in a polymer where the catalyst may exhibit inversion of stereocontrol.