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Imaging Orientation of a Single Molecular Hierarchical Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency Generation Microscopy and Neural Network
[Image: see text] In this work, we determined the tilt angles of molecular units in hierarchical self-assembled materials on a single-sheet level, which were not available previously. This was achieved by developing a fast line-scanning vibrational sum frequency generation (VSFG) hyperspectral imagi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511492/ https://www.ncbi.nlm.nih.gov/pubmed/36098975 http://dx.doi.org/10.1021/acs.jpcb.2c05876 |
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author | Wagner, Jackson C. Wu, Zishan Wang, Haoyuan Xiong, Wei |
author_facet | Wagner, Jackson C. Wu, Zishan Wang, Haoyuan Xiong, Wei |
author_sort | Wagner, Jackson C. |
collection | PubMed |
description | [Image: see text] In this work, we determined the tilt angles of molecular units in hierarchical self-assembled materials on a single-sheet level, which were not available previously. This was achieved by developing a fast line-scanning vibrational sum frequency generation (VSFG) hyperspectral imaging technique in combination with neural network analysis. Rapid VSFG imaging enabled polarization resolved images on a single sheet level to be measured quickly, circumventing technical challenges due to long-term optical instability. The polarization resolved hyperspectral images were then used to extract the supramolecular tilt angle of a self-assembly through a set of spectra-tilt angle relationships which were solved through neural network analysis. This unique combination of both novel techniques offers a new pathway to resolve molecular level structural information on self-assembled materials. Understanding these properties can further drive self-assembly design from a bottom-up approach for applications in biomimetic and drug delivery research. |
format | Online Article Text |
id | pubmed-9511492 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-95114922022-09-27 Imaging Orientation of a Single Molecular Hierarchical Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency Generation Microscopy and Neural Network Wagner, Jackson C. Wu, Zishan Wang, Haoyuan Xiong, Wei J Phys Chem B [Image: see text] In this work, we determined the tilt angles of molecular units in hierarchical self-assembled materials on a single-sheet level, which were not available previously. This was achieved by developing a fast line-scanning vibrational sum frequency generation (VSFG) hyperspectral imaging technique in combination with neural network analysis. Rapid VSFG imaging enabled polarization resolved images on a single sheet level to be measured quickly, circumventing technical challenges due to long-term optical instability. The polarization resolved hyperspectral images were then used to extract the supramolecular tilt angle of a self-assembly through a set of spectra-tilt angle relationships which were solved through neural network analysis. This unique combination of both novel techniques offers a new pathway to resolve molecular level structural information on self-assembled materials. Understanding these properties can further drive self-assembly design from a bottom-up approach for applications in biomimetic and drug delivery research. American Chemical Society 2022-09-13 2022-09-22 /pmc/articles/PMC9511492/ /pubmed/36098975 http://dx.doi.org/10.1021/acs.jpcb.2c05876 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Wagner, Jackson C. Wu, Zishan Wang, Haoyuan Xiong, Wei Imaging Orientation of a Single Molecular Hierarchical Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency Generation Microscopy and Neural Network |
title | Imaging Orientation
of a Single Molecular Hierarchical
Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency
Generation Microscopy and Neural Network |
title_full | Imaging Orientation
of a Single Molecular Hierarchical
Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency
Generation Microscopy and Neural Network |
title_fullStr | Imaging Orientation
of a Single Molecular Hierarchical
Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency
Generation Microscopy and Neural Network |
title_full_unstemmed | Imaging Orientation
of a Single Molecular Hierarchical
Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency
Generation Microscopy and Neural Network |
title_short | Imaging Orientation
of a Single Molecular Hierarchical
Self-Assembled Sheet: The Combined Power of a Vibrational Sum Frequency
Generation Microscopy and Neural Network |
title_sort | imaging orientation
of a single molecular hierarchical
self-assembled sheet: the combined power of a vibrational sum frequency
generation microscopy and neural network |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9511492/ https://www.ncbi.nlm.nih.gov/pubmed/36098975 http://dx.doi.org/10.1021/acs.jpcb.2c05876 |
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