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Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol
Structurally characterizing new materials is tremendously challenging, especially when single crystal structures are hardly available which is often the case for covalent organic frameworks. Yet, knowledge of the atomic structure is key to establish structure‐function relations and enable functional...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048908/ https://www.ncbi.nlm.nih.gov/pubmed/33493379 http://dx.doi.org/10.1002/anie.202017153 |
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author | Borgmans, Sander Rogge, Sven M. J. De Vos, Juul S. Stevens, Christian V. Van Der Voort, Pascal Van Speybroeck, Veronique |
author_facet | Borgmans, Sander Rogge, Sven M. J. De Vos, Juul S. Stevens, Christian V. Van Der Voort, Pascal Van Speybroeck, Veronique |
author_sort | Borgmans, Sander |
collection | PubMed |
description | Structurally characterizing new materials is tremendously challenging, especially when single crystal structures are hardly available which is often the case for covalent organic frameworks. Yet, knowledge of the atomic structure is key to establish structure‐function relations and enable functional material design. Herein, a new protocol is proposed to unambiguously predict the structure of poorly crystalline materials through a likelihood ordering based on the X‐ray diffraction (XRD) pattern. Key of the procedure is the broad set of structures generated from a limited number of building blocks and topologies, which is submitted to operando structural characterization. The dynamic averaging in the latter accounts for the operando conditions and inherent temporal character of experimental measurements, yielding unparalleled agreement with experimental powder XRD patterns. The proposed concept can hence unquestionably identify the structure of experimentally synthesized materials, a crucial step to design next generation functional materials. |
format | Online Article Text |
id | pubmed-8048908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80489082021-04-20 Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol Borgmans, Sander Rogge, Sven M. J. De Vos, Juul S. Stevens, Christian V. Van Der Voort, Pascal Van Speybroeck, Veronique Angew Chem Int Ed Engl Research Articles Structurally characterizing new materials is tremendously challenging, especially when single crystal structures are hardly available which is often the case for covalent organic frameworks. Yet, knowledge of the atomic structure is key to establish structure‐function relations and enable functional material design. Herein, a new protocol is proposed to unambiguously predict the structure of poorly crystalline materials through a likelihood ordering based on the X‐ray diffraction (XRD) pattern. Key of the procedure is the broad set of structures generated from a limited number of building blocks and topologies, which is submitted to operando structural characterization. The dynamic averaging in the latter accounts for the operando conditions and inherent temporal character of experimental measurements, yielding unparalleled agreement with experimental powder XRD patterns. The proposed concept can hence unquestionably identify the structure of experimentally synthesized materials, a crucial step to design next generation functional materials. John Wiley and Sons Inc. 2021-03-08 2021-04-12 /pmc/articles/PMC8048908/ /pubmed/33493379 http://dx.doi.org/10.1002/anie.202017153 Text en © 2021 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Borgmans, Sander Rogge, Sven M. J. De Vos, Juul S. Stevens, Christian V. Van Der Voort, Pascal Van Speybroeck, Veronique Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol |
title | Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol |
title_full | Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol |
title_fullStr | Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol |
title_full_unstemmed | Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol |
title_short | Quantifying the Likelihood of Structural Models through a Dynamically Enhanced Powder X‐Ray Diffraction Protocol |
title_sort | quantifying the likelihood of structural models through a dynamically enhanced powder x‐ray diffraction protocol |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048908/ https://www.ncbi.nlm.nih.gov/pubmed/33493379 http://dx.doi.org/10.1002/anie.202017153 |
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