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Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods

Monte Carlo (MC) methods, based on random updates and the trial-and-error principle, are well suited to retrieve form-free particle size distributions from small-angle scattering patterns of non-interacting low-concentration scatterers such as particles in solution or precipitates in metals. Improve...

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Detalles Bibliográficos
Autores principales: Pauw, Brian R., Pedersen, Jan Skov, Tardif, Samuel, Takata, Masaki, Iversen, Bo B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627408/
https://www.ncbi.nlm.nih.gov/pubmed/23596341
http://dx.doi.org/10.1107/S0021889813001295
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author Pauw, Brian R.
Pedersen, Jan Skov
Tardif, Samuel
Takata, Masaki
Iversen, Bo B.
author_facet Pauw, Brian R.
Pedersen, Jan Skov
Tardif, Samuel
Takata, Masaki
Iversen, Bo B.
author_sort Pauw, Brian R.
collection PubMed
description Monte Carlo (MC) methods, based on random updates and the trial-and-error principle, are well suited to retrieve form-free particle size distributions from small-angle scattering patterns of non-interacting low-concentration scatterers such as particles in solution or precipitates in metals. Improvements are presented to existing MC methods, such as a non-ambiguous convergence criterion, nonlinear scaling of contributions to match their observability in a scattering measurement, and a method for estimating the minimum visibility threshold and uncertainties on the resulting size distributions.
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spelling pubmed-36274082013-04-17 Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods Pauw, Brian R. Pedersen, Jan Skov Tardif, Samuel Takata, Masaki Iversen, Bo B. J Appl Crystallogr Research Papers Monte Carlo (MC) methods, based on random updates and the trial-and-error principle, are well suited to retrieve form-free particle size distributions from small-angle scattering patterns of non-interacting low-concentration scatterers such as particles in solution or precipitates in metals. Improvements are presented to existing MC methods, such as a non-ambiguous convergence criterion, nonlinear scaling of contributions to match their observability in a scattering measurement, and a method for estimating the minimum visibility threshold and uncertainties on the resulting size distributions. International Union of Crystallography 2013-04-01 2013-02-14 /pmc/articles/PMC3627408/ /pubmed/23596341 http://dx.doi.org/10.1107/S0021889813001295 Text en © Brian R. Pauw et al. 2013 http://creativecommons.org/licenses/by/2.0/uk/ This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.
spellingShingle Research Papers
Pauw, Brian R.
Pedersen, Jan Skov
Tardif, Samuel
Takata, Masaki
Iversen, Bo B.
Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods
title Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods
title_full Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods
title_fullStr Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods
title_full_unstemmed Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods
title_short Improvements and considerations for size distribution retrieval from small-angle scattering data by Monte Carlo methods
title_sort improvements and considerations for size distribution retrieval from small-angle scattering data by monte carlo methods
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627408/
https://www.ncbi.nlm.nih.gov/pubmed/23596341
http://dx.doi.org/10.1107/S0021889813001295
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