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**Harvard**

Röding, M., Bernin, D., Jonasson, J., Särkkä, A., Topgaard, D., Rudemo, M. och Nydén, M. (2012) *The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers*.

** BibTeX **

@article{

Röding2012,

author={Röding, Magnus and Bernin, Diana and Jonasson, Jenny and Särkkä, Aila and Topgaard, D. and Rudemo, Mats and Nydén, Magnus},

title={The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers},

journal={Journal of Magnetic Resonance},

issn={1090-7807},

volume={222},

pages={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 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.},

year={2012},

keywords={Pulsed-field gradient NMR, Self-diffusion, PEG, Polymer, Gamma distribution, Log-normal distribution, nuclear-magnetic-resonance, self-diffusion, integral-equations, spin-echo, water, polydispersity, cellulose},

}

** RefWorks **

RT Journal Article

SR Electronic

ID 164550

A1 Röding, Magnus

A1 Bernin, Diana

A1 Jonasson, Jenny

A1 Särkkä, Aila

A1 Topgaard, D.

A1 Rudemo, Mats

A1 Nydén, Magnus

T1 The gamma distribution model for pulsed-field gradient NMR studies of molecular-weight distributions of polymers

YR 2012

JF Journal of Magnetic Resonance

SN 1090-7807

VO 222

SP 105

OP 111

AB 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.

LA eng

DO 10.1016/j.jmr.2012.07.005

LK http://dx.doi.org/10.1016/j.jmr.2012.07.005

LK http://gup.ub.gu.se/records/fulltext/164550.pdf

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