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Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a qua...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348877/ https://www.ncbi.nlm.nih.gov/pubmed/35974742 http://dx.doi.org/10.1107/S160057672200499X |
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author | Deumer, Jérôme Pauw, Brian R. Marguet, Sylvie Skroblin, Dieter Taché, Olivier Krumrey, Michael Gollwitzer, Christian |
author_facet | Deumer, Jérôme Pauw, Brian R. Marguet, Sylvie Skroblin, Dieter Taché, Olivier Krumrey, Michael Gollwitzer, Christian |
author_sort | Deumer, Jérôme |
collection | PubMed |
description | A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm. |
format | Online Article Text |
id | pubmed-9348877 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-93488772022-08-15 Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula Deumer, Jérôme Pauw, Brian R. Marguet, Sylvie Skroblin, Dieter Taché, Olivier Krumrey, Michael Gollwitzer, Christian J Appl Crystallogr Research Papers A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm. International Union of Crystallography 2022-07-15 /pmc/articles/PMC9348877/ /pubmed/35974742 http://dx.doi.org/10.1107/S160057672200499X Text en © Jérôme Deumer et al. 2022 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Research Papers Deumer, Jérôme Pauw, Brian R. Marguet, Sylvie Skroblin, Dieter Taché, Olivier Krumrey, Michael Gollwitzer, Christian Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula |
title | Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula |
title_full | Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula |
title_fullStr | Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula |
title_full_unstemmed | Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula |
title_short | Small-angle X-ray scattering: characterization of cubic Au nanoparticles using Debye’s scattering formula |
title_sort | small-angle x-ray scattering: characterization of cubic au nanoparticles using debye’s scattering formula |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348877/ https://www.ncbi.nlm.nih.gov/pubmed/35974742 http://dx.doi.org/10.1107/S160057672200499X |
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