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An insight into Ziegler–Natta catalyst active site distribution for polyolefins: application of jitter differential evolution

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Abstract

Most commercial polyolefins are made with heterogeneous Ziegler–Natta and metallocene catalysts with narrow to broad molecular weight distribution due to the presence of several active sites in the catalyst. We have carried out deconvolution of the molecular weight distribution (MWD) curves from gel permeation chromatography into distributions for individual active sites considering Flory distribution. Polyolefin from three different types of catalysts—(1) propylene and propylene/1-octene copolymer using MgCl2-supported Ti catalyst, (2) linear low-density polyethylene (LLDPE) by silica-supported Ti catalyst and (3) LLDPE by silica-supported metallocene catalyst—is considered for deconvolution studies. A robust jitter differential evolution (JDE) method-based computer algorithm is developed to deconvolute the MWD curves into various Flory distributions. The investigation gave insights on the active sites distribution, peak molecular weight and ratio of termination to propagation rate of each active site. Our analysis has shown that five individual Flory distributions provide PP and LLDPE with better than a 99.9% degree of fit. We have also rolled out this deconvolution method with a simple Excel sheet based input on a cloud-based interface. The results show that JDE approach is a powerful tool to decipher the role of catalyst active sites and correlate with polymer characteristics.

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Authors and Affiliations

  1. Reliance Research and Development Centre, Reliance Corporate Park, Reliance Industries Limited (RIL), Thane Belapur Road, Navi Mumbai, India

    Harshad R. Patil, Sangeetha Karthikeyan, Vikas Kote, Pratyay Sengupta, Pratyagra Samanta, Pooja Kadam, Natarajan Venkateswaran & Virendra Kumar Gupta

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  1. Harshad R. Patil
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Patil, H.R., Karthikeyan, S., Kote, V. et al. An insight into Ziegler–Natta catalyst active site distribution for polyolefins: application of jitter differential evolution. Polym. Bull. 80, 1425–1445 (2023). https://doi.org/10.1007/s00289-022-04107-3

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