Display options
Cite
Urbańczyk M, Bernin D, Czuroń A, et al. Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing. Analyst. 2016;141(5):1745-52doi: 10.1039/c5an02304a.
Urbańczyk, M., Bernin, D., Czuroń, A., & Kazimierczuk, K. (2016). Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing. The Analyst, 141(5), 1745-52. https://doi.org/10.1039/c5an02304a
Urbańczyk, Mateusz, et al. "Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing." The Analyst vol. 141,5 (2016): 1745-52. doi: https://doi.org/10.1039/c5an02304a
Urbańczyk M, Bernin D, Czuroń A, Kazimierczuk K. Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing. Analyst. 2016 Mar 07;141(5):1745-52. doi: 10.1039/c5an02304a. PMID: 26824089.
Copy Download .nbib Format: NLM
Share it on

Analyst. 2016 Mar 07;141(5):1745-52. doi: 10.1039/c5an02304a.

Monitoring polydispersity by NMR diffusometry with tailored norm regularisation and moving-frame processing.

The Analyst

Mateusz Urbańczyk, Diana Bernin, Alan Czuroń, Krzysztof Kazimierczuk

Affiliations

  1. Faculty of Chemistry, Biological and Chemical Research Centre, University of Warsaw, ?wirki i Wigury 101, 02-089 Warszawa, Poland and Centre of New Technologies, University of Warsaw, ul. Banacha 2C, 02-097 Warsaw, Poland. [email protected].
  2. Swedish NMR Centre, University of Gothenburg, Box 465, 40530 Göteborg, Sweden.
  3. Institute of Mathematics, Polish Academy of Sciences, ul. Sniadeckich 8, 00-656 Warszawa, Poland.
  4. Centre of New Technologies, University of Warsaw, ul. Banacha 2C, 02-097 Warsaw, Poland. [email protected].

PMID: 26824089 DOI: 10.1039/c5an02304a

Abstract

Nuclear magnetic resonance (NMR) is currently one of the main analytical techniques applied in numerous branches of chemistry. Furthermore, NMR has been proven to be useful to follow in situ reactions occurring on a time scale of hours and days. For complicated mixtures, NMR experiments providing diffusion coefficients are particularly advantageous. However, the inverse Laplace transform (ILT) that is used to extract the distribution of diffusion coefficients from an NMR signal is known to be unstable and vulnerable to noise. Numerous regularisation techniques to circumvent this problem have been proposed. In our recent study, we proposed a method based on sparsity-enforcing l1-norm minimisation. This approach, which is referred to as ITAMeD, has been successful but limited to samples with a 'discrete' distribution of diffusion coefficients. In this paper, we propose a generalisation of ITAMeD using a tailored lp-norm (1 ≤ p ≤ 2) to process, in particular, signals arising from 'polydisperse' samples. The performance of our method was tested on simulations and experimental datasets of polyethylene oxides with varying polydispersity indices. Finally, we applied our new method to monitor diffusion coefficient and polydispersity changes of heparin undergoing enzymatic degradation in real time.

Publication Types