Microscopic observation of the segmental orientation autocorrelation function for entangled and constrained polymer chains

Anton Mordvinkin,Kay Saalwächter

doi:10.1063/1.4977041

Abstract

Previous work on probing the dynamics of reptating polymer chains in terms of the segmental orientation autocorrelation function (OACF) by multiple-quantum (MQ) NMR relied on the time-temperature superposition (TTS) principle as applied to normalized double-quantum (DQ) build-up curves. Alternatively, an initial-rise analysis of the latter is also possible. These approaches are subject to uncertainties related to the relevant segmental shift factor or parasitic signals and inhomogeneities distorting the build-up at short times, respectively. Here, we present a simple analytical fitting approach based upon a power-law model of the OACF, by the way of which an effective power-law time scaling exponent and the amplitude of the OACF can be estimated from MQ NMR data at any given temperature. This obviates the use of TTS and provides a robust and independent probe of the shape of the OACF. The approach is validated by application to polymer melts of variable molecular weight as well as elastomers. We anticipate a wide range of applications, including the study of physical networks with labile junctions.

Highlights

Polymers, due to their chain structure, exhibit dynamics over a wide range of time scales covering more than ten decades
Previous work on probing the dynamics of reptating polymer chains in terms of the segmental orientation autocorrelation function (OACF) by multiple-quantum (MQ) NMR relied on the timetemperature superposition (TTS) principle as applied to normalized double-quantum (DQ) build-up curves
A new analytical fitting approach based upon a simple power-law model for the segmental orientation autocorrelation function (OACF) was implemented and applied to various 1H MQ NMR data sets measured on polymer melt and elastomer samples in order to extract dynamic information on the shape of the OACF, its amplitude and approximate power-law exponent

Summary

INTRODUCTION

Due to their chain structure, exhibit dynamics over a wide range of time scales covering more than ten decades. The tube model of entangled polymers provides a microscopic description of the chain dynamics within this large time window, thereby distinguishing different regimes with characteristic scaling exponents of the segmental mean-square displacement. Good adherence to tube model predictions was found only for the former, in some contrast to in principle equivalent MQ NMR results as well as different computer simulations.. Good adherence to tube model predictions was found only for the former, in some contrast to in principle equivalent MQ NMR results as well as different computer simulations.17,18 The origin of this discrepancy is yet to be elucidated, calling for a concerted multi-method approach. Spurious signal contributions or sample inhomogeneities can completely hamper such an isothermal assessment of κ In this contribution, building upon earlier work on polymer networks, we present. We illustrate its feasibility on the example of theoretical meta-data and demonstrate its superior robustness by the analysis of previous data for entangled polymer melts as well as homogeneous and inhomogeneous (swollen) elastomers

BASIC PRINCIPLES OF MQ NMR

RESULTS AND DISCUSSION

CONCLUSIONS