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Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method

A Monte Carlo (MC) method was introduced into a state-of-the-art model used to analyse small-angle X-ray scattering (SAXS) data of SBA-15, an ordered mesoporous material with many applications. With this new procedure, referred to herein as the SBA-15+MC model, it is possible to retrieve the size di...

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Autores principales: Tan, Xiangyin, Gerbelli, Barbara Bianca, Fantini, Márcia Carvalho de Abreu, Oliveira, Cristiano Luis Pinto, Bordallo, Heloísa Nunes, Oseliero Filho, Pedro Leonidas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543675/
https://www.ncbi.nlm.nih.gov/pubmed/37791357
http://dx.doi.org/10.1107/S160057672300691X
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author Tan, Xiangyin
Gerbelli, Barbara Bianca
Fantini, Márcia Carvalho de Abreu
Oliveira, Cristiano Luis Pinto
Bordallo, Heloísa Nunes
Oseliero Filho, Pedro Leonidas
author_facet Tan, Xiangyin
Gerbelli, Barbara Bianca
Fantini, Márcia Carvalho de Abreu
Oliveira, Cristiano Luis Pinto
Bordallo, Heloísa Nunes
Oseliero Filho, Pedro Leonidas
author_sort Tan, Xiangyin
collection PubMed
description A Monte Carlo (MC) method was introduced into a state-of-the-art model used to analyse small-angle X-ray scattering (SAXS) data of SBA-15, an ordered mesoporous material with many applications. With this new procedure, referred to herein as the SBA-15+MC model, it is possible to retrieve the size distribution of the mesopores, D(r), in a free modelling approach. To achieve this, two main points were addressed: (i) based on previous implementations, the method was adapted to work with long core–shell cylinders; (ii) since the MC model requires longer processing times, strategies to speed up the calculations were developed, which included a simplified version of the original model used to analyse SAXS data of SBA-15 (referred to as the SBA-15 model) as well as the determination of several structural features from the SAXS curve prior to the fit. The new model was validated with simulated data and later used to fit experimental SAXS curves of SBA-15. The obtained results show that the SBA-15 model only works well because the mesopore size distribution of SBA-15 is narrow, whereas the new approach can be successfully used in cases where D(r) is wider and/or has a more complex profile, such as SBA-15 with expanded mesopores. Even though a specific SAXS example was chosen to prove the model, the strategies presented herein are general and suitable for inclusion in other models aimed at the analysis of SBA-15 and similar ordered mesoporous materials.
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spelling pubmed-105436752023-10-03 Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method Tan, Xiangyin Gerbelli, Barbara Bianca Fantini, Márcia Carvalho de Abreu Oliveira, Cristiano Luis Pinto Bordallo, Heloísa Nunes Oseliero Filho, Pedro Leonidas J Appl Crystallogr Research Papers A Monte Carlo (MC) method was introduced into a state-of-the-art model used to analyse small-angle X-ray scattering (SAXS) data of SBA-15, an ordered mesoporous material with many applications. With this new procedure, referred to herein as the SBA-15+MC model, it is possible to retrieve the size distribution of the mesopores, D(r), in a free modelling approach. To achieve this, two main points were addressed: (i) based on previous implementations, the method was adapted to work with long core–shell cylinders; (ii) since the MC model requires longer processing times, strategies to speed up the calculations were developed, which included a simplified version of the original model used to analyse SAXS data of SBA-15 (referred to as the SBA-15 model) as well as the determination of several structural features from the SAXS curve prior to the fit. The new model was validated with simulated data and later used to fit experimental SAXS curves of SBA-15. The obtained results show that the SBA-15 model only works well because the mesopore size distribution of SBA-15 is narrow, whereas the new approach can be successfully used in cases where D(r) is wider and/or has a more complex profile, such as SBA-15 with expanded mesopores. Even though a specific SAXS example was chosen to prove the model, the strategies presented herein are general and suitable for inclusion in other models aimed at the analysis of SBA-15 and similar ordered mesoporous materials. International Union of Crystallography 2023-09-01 /pmc/articles/PMC10543675/ /pubmed/37791357 http://dx.doi.org/10.1107/S160057672300691X Text en © Xiangyin Tan et al. 2023 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
Tan, Xiangyin
Gerbelli, Barbara Bianca
Fantini, Márcia Carvalho de Abreu
Oliveira, Cristiano Luis Pinto
Bordallo, Heloísa Nunes
Oseliero Filho, Pedro Leonidas
Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method
title Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method
title_full Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method
title_fullStr Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method
title_full_unstemmed Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method
title_short Retrieving the size distribution of SBA-15 mesopores from small-angle X-ray scattering data using a Monte Carlo method
title_sort retrieving the size distribution of sba-15 mesopores from small-angle x-ray scattering data using a monte carlo method
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543675/
https://www.ncbi.nlm.nih.gov/pubmed/37791357
http://dx.doi.org/10.1107/S160057672300691X
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