Unraveling Multiple Distributions in Chain Walking Polyethylene Using Advanced Liquid Chromatography

Abstract

Chain-walking (CW) catalysis applied to α-olefin polymerization gives rise to structurally unparalleled macromolecules with diverse topological and rheological properties. The specific motion pattern of the CW catalyst along the polymer chain is easily manipulated by varying synthesis parameters such as monomer concentration, temperature, and time or by adjusting the steric and electronic effects of the catalyst's ligands or choice of central metal. While their structural potential has been extensively studied, the experimental identification has often been single-sided. Modern techniques in liquid chromatography provide a suitable approach to investigate the complex dimensions of CW polyethylene (PE). In this study, advanced interaction chromatography in temperature and solvent gradient modes as well as comprehensive two-dimensional chromatography (2D-LC), coupling of interaction (IC), and size exclusion chromatography (SEC) are combined with multidetector high-temperature SEC (HT-SEC) to characterize the multidimensional heterogeneity of CWPE. Nuclear magnetic resonance and Fourier transform infrared spectroscopy provide quantitative information about the types and numbers of branches. The complementary characterization techniques give insight into highly diverse branching topologies within narrow molar mass distributions of the CW polyethylene.

Cost‐efficient modeling of distributed molar mass and topological variations in graft copolymer synthesis by upgrading the method of moments

“…In 2D‐LC, the effluents from the first dimension (1st‐D) need to be analyzed by the second dimension (2nd‐D) following another (ideally orthogonal) separation mode. Here, one separates copolymers by CCs or by MM of the specific monomer sequences (e.g., PB or PS segments in the context of the present work) 73–78 . In this way, the bivariate distributions correlating two different molecular parameters can be accessible so that higher resolution and more informative data are in principle delivered.…”

“…Here, one separates copolymers by CCs or by MM of the specific monomer sequences (e.g., PB or PS segments in the context of the present work). [73][74][75][76][77][78] In this way, the bivariate distributions correlating two different molecular parameters can be accessible so that higher resolution and more informative data are in principle delivered.…”

Multidimensional analytical protocols for the fractionation and analysis of complex polyolefins

“…More examples of HT-2D-HPLC are given in Refs. [104][105][106][107][108][109][110][111][112][113][114][115][116][117][118][119][120].…”

Automated Feature Mining for Two-Dimensional Liquid Chromatography Applied to Polymers Enabled by Mass Remainder Analysis

“…3 − 5 This is because LC × LC allows the simultaneous characterization of multiple molecular characteristics, from determining the molecular weight distribution and chemical composition distribution to functionality and topology distributions. 6 …”