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Resolving sub-angstrom ambient motion through reconstruction from vibrational spectra.

Published version
Peer-reviewed

Type

Article

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Authors

Griffiths, Jack 
Földes, Tamás 
Wright, Demelza 

Abstract

Metal/organic-molecule interactions underpin many key chemistries but occur on sub-nm scales where nanoscale visualisation techniques tend to average over heterogeneous distributions. Single molecule imaging techniques at the atomic scale have found it challenging to track chemical behaviour under ambient conditions. Surface-enhanced Raman spectroscopy can optically monitor the vibrations of single molecules but understanding is limited by the complexity of spectra and mismatch between theory and experiment. We demonstrate that spectra from an optically generated metallic adatom near a molecule of interest can be inverted into dynamic sub-Å metal-molecule interactions using a comprehensive model, revealing anomalous diffusion of a single atom. Transient metal-organic coordination bonds chemically perturb molecular functional groups > 10 bonds away. With continuous improvements in computational methods for modelling large and complex molecular systems, this technique will become increasingly applicable to accurately tracking more complex chemistries.

Description

Keywords

Journal Title

Nat Commun

Conference Name

Journal ISSN

2041-1723
2041-1723

Volume Title

12

Publisher

Springer Science and Business Media LLC
Sponsorship
Isaac Newton Trust (18.08(K))
Leverhulme Trust (ECF-2018-021)
Engineering and Physical Sciences Research Council (EP/G060649/1)
Engineering and Physical Sciences Research Council (EP/L027151/1)
Engineering and Physical Sciences Research Council (EP/G037221/1)
European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (829067)
Engineering and Physical Sciences Research Council (EP/R020965/1)
European Commission Horizon 2020 (H2020) Research Infrastructures (RI) (861950)
European Commission Horizon 2020 (H2020) ERC (883703)
Engineering and Physical Sciences Research Council (EP/L015978/1)
We acknowledge financial support from EPSRC grant EP/G060649/1, EP/L027151/1, EP/G037221/1, EP/R013012/1, EPSRC NanoDTC, and EU grant THOR 829067 and ERC starting grant BioNet 757850. B.d.N. acknowledges support from the Leverhulme Trust and Isaac Newton Trust. We acknowledge use of the Rosalind computing facility at King’s College London. We are grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by EPSRC 397 (EP/P020194/1).
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