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Mapping Atomic-Scale Metal–Molecule Interactions: Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy Data
[Image: see text] Atomic-scale features, such as step edges and adatoms, play key roles in metal–molecule interactions and are critically important in heterogeneous catalysis, molecular electronics, and sensing applications. However, the small size and often transient nature of atomic-scale structur...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476190/ https://www.ncbi.nlm.nih.gov/pubmed/37594383 http://dx.doi.org/10.1021/acs.jpclett.3c01483 |
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author | Poppe, Alex Griffiths, Jack Hu, Shu Baumberg, Jeremy J. Osadchy, Margarita Gibson, Stuart de Nijs, Bart |
author_facet | Poppe, Alex Griffiths, Jack Hu, Shu Baumberg, Jeremy J. Osadchy, Margarita Gibson, Stuart de Nijs, Bart |
author_sort | Poppe, Alex |
collection | PubMed |
description | [Image: see text] Atomic-scale features, such as step edges and adatoms, play key roles in metal–molecule interactions and are critically important in heterogeneous catalysis, molecular electronics, and sensing applications. However, the small size and often transient nature of atomic-scale structures make studying such interactions challenging. Here, by combining single-molecule surface-enhanced Raman spectroscopy with machine learning, spectra are extracted of perturbed molecules, revealing the formation dynamics of adatoms in gold and palladium metal surfaces. This provides unique insight into atomic-scale processes, allowing us to resolve where such metallic protrusions form and how they interact with nearby molecules. Our technique paves the way to tailor metal–molecule interactions on an atomic level and assists in rational heterogeneous catalyst design. |
format | Online Article Text |
id | pubmed-10476190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104761902023-09-05 Mapping Atomic-Scale Metal–Molecule Interactions: Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy Data Poppe, Alex Griffiths, Jack Hu, Shu Baumberg, Jeremy J. Osadchy, Margarita Gibson, Stuart de Nijs, Bart J Phys Chem Lett [Image: see text] Atomic-scale features, such as step edges and adatoms, play key roles in metal–molecule interactions and are critically important in heterogeneous catalysis, molecular electronics, and sensing applications. However, the small size and often transient nature of atomic-scale structures make studying such interactions challenging. Here, by combining single-molecule surface-enhanced Raman spectroscopy with machine learning, spectra are extracted of perturbed molecules, revealing the formation dynamics of adatoms in gold and palladium metal surfaces. This provides unique insight into atomic-scale processes, allowing us to resolve where such metallic protrusions form and how they interact with nearby molecules. Our technique paves the way to tailor metal–molecule interactions on an atomic level and assists in rational heterogeneous catalyst design. American Chemical Society 2023-08-18 /pmc/articles/PMC10476190/ /pubmed/37594383 http://dx.doi.org/10.1021/acs.jpclett.3c01483 Text en © 2023 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 | Poppe, Alex Griffiths, Jack Hu, Shu Baumberg, Jeremy J. Osadchy, Margarita Gibson, Stuart de Nijs, Bart Mapping Atomic-Scale Metal–Molecule Interactions: Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy Data |
title | Mapping Atomic-Scale
Metal–Molecule Interactions:
Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy
Data |
title_full | Mapping Atomic-Scale
Metal–Molecule Interactions:
Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy
Data |
title_fullStr | Mapping Atomic-Scale
Metal–Molecule Interactions:
Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy
Data |
title_full_unstemmed | Mapping Atomic-Scale
Metal–Molecule Interactions:
Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy
Data |
title_short | Mapping Atomic-Scale
Metal–Molecule Interactions:
Salient Feature Extraction through Autoencoding of Vibrational Spectroscopy
Data |
title_sort | mapping atomic-scale
metal–molecule interactions:
salient feature extraction through autoencoding of vibrational spectroscopy
data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476190/ https://www.ncbi.nlm.nih.gov/pubmed/37594383 http://dx.doi.org/10.1021/acs.jpclett.3c01483 |
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