Simultaneous Deconvolution of the Molecular Weight and Chemical Composition Distribution of Polyolefins Made with Ziegler-Natta Catalysts

Heterogeneous Ziegler-Natta catalysts produce polyolefins that have broad distributions of molecular weight (MWD) and chemical composition (CCD). For such broad distributions, mathematical models are useful to quantify the information provided by polyolefin analytical techniques such as high-temperature gel permeation chromatography (GPC), temperature rising elution fractionation (TREF), and crystallization analysis fractionation (CRYSTAF). In this paper, we developed a mathematical model to deconvolute the MWD and CCD of polyolefins simultaneously, using Flory's most probable distribution and the cumulative CCD component of Stockmayer's distribution. We have applied this procedure to “model” polyolefin resins and to one industrial linear low-density polyethylene (LLDPE) resin. The proposed methodology is able to deconvolute theoretical distributions even when random noise is added to the MWDs and CCDs, and it can be used to calculate the minimum number of active site types on heterogeneous Ziegler-Natta catalysts.