Correlation Between Segmental Order Parameter and Entanglement Length in a Monodisperse Comb Polymer

This Dataset comprises the raw data contained in the figures of our journal article in Macromolecules 2024 (DOI: 10.1021/acs.macromol.4c02015) and its Supporting Information (SI). We provide a preprint of the initially submitted article including the SI for reference to the figures and their captions, necessary to use the data. Note that Fig. S1 was added upon revision, so Fig. S2 of the published SI is Fig. S1 of the SI that is part of the preprint. Please also check the published article in Macromolecules. For copyright details and licensing we refer to the published article and the publisher. Here is the abstract of the article: The motion of a polymer chain within a hypothetical confining tube leads to arise a segmental order parameter. This parameter is assessed via multiple-quantum (MQ) NMR experiments. In both polymer networks and entangled melts, the order parameter is proportional to the inverse of the number of segments between two covalent crosslinks or physical entanglements. In entangled polymer networks, the entanglements have usually been considered as additional but temporary crosslinks and the contribution of the physical and chemical constraints are assumed additive. However, it was revealed by computer simulation results that this assumption is not valid for lowly crosslinked polymer networks; instead, the segmental order parameter was shown to scale with 1/√(N_e N_c ), N_c and N_e being the number of segments between crosslinks and entanglements, respectively [M. Lang and J.-U. Sommer, Phys. Rev. Lett. 2010, 104, 177801]. An experimental confirmation remains elusive due to challenges in distinguishing the contributions of entanglements and crosslinks, as well as the long averaging timescales involved. In this study, we assess this correlation by examining chain dynamics in a monodisperse polyisoprene comb, utilized as a model system. To model chain dynamics in this system, the dynamic dilution model, originally designed for predicting the rheological behavior of star and branched polymers, has been modified to facilitate its application in the analysis of MQ NMR signals. We also address some of its shortcomings.