Polyolefin microstructural deconvolution methods: The good, the bad, and the ugly
João B. P. Soares
Abstract
Abstract The deconvolution of the molecular weight distribution (MWD) of polyolefins into Schultz–Flory most probable distributions has become the standard method to identify the number of site types on multiple‐site‐type olefin polymerization catalysts such as Ziegler–Natta, Phillips, and some supported metallocenes. This method has been used to quantify the effect of polymerization conditions and catalyst formulations on polyolefin MWD and olefin polymerization kinetics. Related methods have also been developed to deconvolute other polyolefin microstructure features, such as the chemical composition and comonomer sequence length distributions. In this paper, I explain the premises behind these deconvolution models and review the publications in this area, highlighting the advantages, disadvantages, and misuses of these methods. I also propose a revised formulation on how to model the MWD of polyolefins made with multiple‐site‐type catalysts using ratio distributions for propagation and chain transfer frequencies. The main objective of this overview article is to highlight the strengths, but also show the pitfalls, of polyolefin microstructure deconvolution methods.