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Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films

Grazing-incidence small-angle X-ray scattering (GISAXS) is a widely used method for the characterization of the nanostructure of supported thin films and enables time-resolved in situ measurements. The 2D scattering patterns contain detailed information about the nanostructures within the film and a...

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Autores principales: Jung, Florian A., Papadakis, Christine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543672/
https://www.ncbi.nlm.nih.gov/pubmed/37791363
http://dx.doi.org/10.1107/S1600576723006520
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author Jung, Florian A.
Papadakis, Christine M.
author_facet Jung, Florian A.
Papadakis, Christine M.
author_sort Jung, Florian A.
collection PubMed
description Grazing-incidence small-angle X-ray scattering (GISAXS) is a widely used method for the characterization of the nanostructure of supported thin films and enables time-resolved in situ measurements. The 2D scattering patterns contain detailed information about the nanostructures within the film and at its surface. However, this information is distorted not only by the reflection of the X-ray beam at the substrate–film interface and its refraction at the film surface but also by scattering of the substrate, the sample holder and other types of parasitic background scattering. In this work, a new, efficient strategy to simulate and fit 2D GISAXS patterns that explicitly includes these effects is introduced and demonstrated for (i) a model case nanostructured thin film on a substrate and (ii) experimental data from a microphase-separated block copolymer thin film. To make the protocol efficient, characteristic linecuts through the 2D GISAXS patterns, where the different contributions dominate, are analysed. The contributions of the substrate and the parasitic background scattering – which ideally are measured separately – are determined first and are used in the analysis of the 2D GISAXS patterns of the nanostructured, supported film. The nanostructures at the film surface and within the film are added step by step to the real-space model of the simulation, and their structural parameters are determined by minimizing the difference between simulated and experimental scattering patterns in the selected linecuts. Although in the present work the strategy is adapted for and tested with BornAgain, it can be easily used with other types of simulation software. The strategy is also applicable to grazing-incidence small-angle neutron scattering.
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spelling pubmed-105436722023-10-03 Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films Jung, Florian A. Papadakis, Christine M. J Appl Crystallogr Research Papers Grazing-incidence small-angle X-ray scattering (GISAXS) is a widely used method for the characterization of the nanostructure of supported thin films and enables time-resolved in situ measurements. The 2D scattering patterns contain detailed information about the nanostructures within the film and at its surface. However, this information is distorted not only by the reflection of the X-ray beam at the substrate–film interface and its refraction at the film surface but also by scattering of the substrate, the sample holder and other types of parasitic background scattering. In this work, a new, efficient strategy to simulate and fit 2D GISAXS patterns that explicitly includes these effects is introduced and demonstrated for (i) a model case nanostructured thin film on a substrate and (ii) experimental data from a microphase-separated block copolymer thin film. To make the protocol efficient, characteristic linecuts through the 2D GISAXS patterns, where the different contributions dominate, are analysed. The contributions of the substrate and the parasitic background scattering – which ideally are measured separately – are determined first and are used in the analysis of the 2D GISAXS patterns of the nanostructured, supported film. The nanostructures at the film surface and within the film are added step by step to the real-space model of the simulation, and their structural parameters are determined by minimizing the difference between simulated and experimental scattering patterns in the selected linecuts. Although in the present work the strategy is adapted for and tested with BornAgain, it can be easily used with other types of simulation software. The strategy is also applicable to grazing-incidence small-angle neutron scattering. International Union of Crystallography 2023-08-16 /pmc/articles/PMC10543672/ /pubmed/37791363 http://dx.doi.org/10.1107/S1600576723006520 Text en © Jung and Papadakis 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
Jung, Florian A.
Papadakis, Christine M.
Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films
title Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films
title_full Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films
title_fullStr Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films
title_full_unstemmed Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films
title_short Strategy to simulate and fit 2D grazing-incidence small-angle X-ray scattering patterns of nanostructured thin films
title_sort strategy to simulate and fit 2d grazing-incidence small-angle x-ray scattering patterns of nanostructured thin films
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10543672/
https://www.ncbi.nlm.nih.gov/pubmed/37791363
http://dx.doi.org/10.1107/S1600576723006520
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