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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.
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Mordvinkin et al. (2017) studied this question.
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