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The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers

Roding, Magnus; Bernin, Diana; Jonasson, Jenny; Sarkka, Aila; Topgaard, Daniel LU ; Rudemo, Mats and Nyden, Magnus (2012) In Journal of Magnetic Resonance 222. p.105-111
Abstract
Self-diffusion in polymer solutions studied with pulsed-field gradient nuclear magnetic resonance (PFG NMR) is typically based either on a single self-diffusion coefficient, or a log-normal distribution of self-diffusion coefficients, or in some cases mixtures of these. Experimental data on polyethylene glycol (PEG) solutions and simulations were used to compare a model based on a gamma distribution of self-diffusion coefficients to more established models such as the single exponential, the stretched exponential, and the log-normal distribution model with regard to performance and consistency. Even though the gamma distribution is very similar to the log-normal distribution, its NMR signal attenuation can be written in a closed form and... (More)
Self-diffusion in polymer solutions studied with pulsed-field gradient nuclear magnetic resonance (PFG NMR) is typically based either on a single self-diffusion coefficient, or a log-normal distribution of self-diffusion coefficients, or in some cases mixtures of these. Experimental data on polyethylene glycol (PEG) solutions and simulations were used to compare a model based on a gamma distribution of self-diffusion coefficients to more established models such as the single exponential, the stretched exponential, and the log-normal distribution model with regard to performance and consistency. Even though the gamma distribution is very similar to the log-normal distribution, its NMR signal attenuation can be written in a closed form and therefore opens up for increased computational speed. Estimates of the mean self-diffusion coefficient, the spread, and the polydispersity index that were obtained using the gamma model were in excellent agreement with estimates obtained using the log-normal model. Furthermore, we demonstrate that the gamma distribution is by far superior to the log-normal, and comparable to the two other models, in terms of computational speed. This effect is particularly striking for multi-component signal attenuation. Additionally, the gamma distribution as well as the log-normal distribution incorporates explicitly a physically plausible model for polydispersity and spread, in contrast to the single exponential and the stretched exponential. Therefore, the gamma distribution model should be preferred in many experimental situations. (C) 2012 Elsevier Inc. All rights reserved. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Pulsed-field gradient NMR, Self-diffusion, PEG, Polymer, Gamma, distribution, Log-normal distribution, Molecular-weight distribution
in
Journal of Magnetic Resonance
volume
222
pages
105 - 111
publisher
Elsevier
external identifiers
  • wos:000308120300014
  • scopus:84865144697
ISSN
1096-0856
DOI
10.1016/j.jmr.2012.07.005
language
English
LU publication?
yes
id
09402644-cc4f-47e1-ae1f-eac67d1fdc7b (old id 3146855)
date added to LUP
2012-11-26 09:32:06
date last changed
2017-11-05 04:02:52
@article{09402644-cc4f-47e1-ae1f-eac67d1fdc7b,
  abstract     = {Self-diffusion in polymer solutions studied with pulsed-field gradient nuclear magnetic resonance (PFG NMR) is typically based either on a single self-diffusion coefficient, or a log-normal distribution of self-diffusion coefficients, or in some cases mixtures of these. Experimental data on polyethylene glycol (PEG) solutions and simulations were used to compare a model based on a gamma distribution of self-diffusion coefficients to more established models such as the single exponential, the stretched exponential, and the log-normal distribution model with regard to performance and consistency. Even though the gamma distribution is very similar to the log-normal distribution, its NMR signal attenuation can be written in a closed form and therefore opens up for increased computational speed. Estimates of the mean self-diffusion coefficient, the spread, and the polydispersity index that were obtained using the gamma model were in excellent agreement with estimates obtained using the log-normal model. Furthermore, we demonstrate that the gamma distribution is by far superior to the log-normal, and comparable to the two other models, in terms of computational speed. This effect is particularly striking for multi-component signal attenuation. Additionally, the gamma distribution as well as the log-normal distribution incorporates explicitly a physically plausible model for polydispersity and spread, in contrast to the single exponential and the stretched exponential. Therefore, the gamma distribution model should be preferred in many experimental situations. (C) 2012 Elsevier Inc. All rights reserved.},
  author       = {Roding, Magnus and Bernin, Diana and Jonasson, Jenny and Sarkka, Aila and Topgaard, Daniel and Rudemo, Mats and Nyden, Magnus},
  issn         = {1096-0856},
  keyword      = {Pulsed-field gradient NMR,Self-diffusion,PEG,Polymer,Gamma,distribution,Log-normal distribution,Molecular-weight distribution},
  language     = {eng},
  pages        = {105--111},
  publisher    = {Elsevier},
  series       = {Journal of Magnetic Resonance},
  title        = {The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers},
  url          = {http://dx.doi.org/10.1016/j.jmr.2012.07.005},
  volume       = {222},
  year         = {2012},
}