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The lognormal and gamma distribution models for estimating molecular weight distributions of polymers using PGSE NMR
Future Industries Institute, University of South Australia.
Future Industries Institute, University of South Australia; School of Energy and Resources, UCL Australia, University College London.
RISE, SP – Sveriges Tekniska Forskningsinstitut, SP Food and Bioscience. Future Industries Institute, University of South Australia; School of Energy and Resources, UCL Australia, University College London.
2016 (English)In: Journal of magnetic resonance, ISSN 1090-7807, E-ISSN 1096-0856, Vol. 267, 54-62 p.Article in journal (Refereed) Published
Abstract [en]

We present comprehensive derivations for the statistical models and methods for the use of pulsed gradient spin echo (PGSE) NMR to characterize the molecular weight distribution of polymers via the well-known scaling law relating diffusion coefficients and molecular weights. We cover the lognormal and gamma distribution models and linear combinations of these distributions. Although the focus is on methodology, we illustrate the use experimentally with three polystyrene samples, comparing the NMR results to gel permeation chromatography (GPC) measurements, test the accuracy and noise-sensitivity on simulated data, and provide code for implementation. © 2016 Elsevier Inc. All rights reserved.

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Academic Press, 2016. Vol. 267, 54-62 p.
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Natural Sciences
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URN: urn:nbn:se:ri:diva-321DOI: 10.1016/j.jmr.2016.04.007OAI: oai:DiVA.org:ri-321DiVA: diva2:938731
Available from: 2016-06-17 Created: 2016-06-17 Last updated: 2017-11-28Bibliographically approved

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