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  Fully Ab initio Simulations of Tip Enhanced Raman Scattering Reveal Active Role of Substrate on High-Resolution Images

Litman, Y., Bonafé, F., Akkoush, A., Appel, H., & Rossi, M. (2022). Fully Ab initio Simulations of Tip Enhanced Raman Scattering Reveal Active Role of Substrate on High-Resolution Images.

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2211.09475.pdf (Preprint), 17MB
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2211.09475.pdf
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File downloaded from arXiv at 2022-11-22
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https://arxiv.org/abs/2211.09475 (Preprint)
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 Creators:
Litman, Y.1, 2, Author           
Bonafé, F.3, Author           
Akkoush, A.2, 4, Author           
Appel, H.3, Author           
Rossi, M.2, 4, Author           
Affiliations:
1Yusuf Hamied Department of Chemistry, University of Cambridge, ou_persistent22              
2Simulations from Ab Initio Approaches, Theory Department, Max Planck Institute for the Structure and Dynamics of Matter, Max Planck Society, ou_3185035              
3Theory Group, Theory Department, Max Planck Institute for the Structure and Dynamics of Matter, Max Planck Society, ou_2266715              
4Fritz Haber Institute of the Max Planck Society, ou_persistent22              

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Free keywords: Physics, Chemical Physics, physics.chem-ph
 Abstract: Tip-enhanced Raman scattering (TERS) has emerged as a powerful tool to obtain subnanometer spatial resolution fingerprints of atomic motion. Theoretical calculations that can simulate the Raman scattering process and provide an unambiguous interpretation of TERS images often rely on crude approximations of the local electric field. In this work, we present a novel and fully ab initio method to compute TERS images by combining Time Dependent Density Functional Theory (TD-DFT) and Density Functional Perturbation Theory (DFPT) to calculate Raman cross sections with realistic local fields. We present TERS results on the benzene and the TCNE molecule, the latter adsorbed at Ag(110). We demonstrate that chemical effects on adsorbed molecules, often ignored in TERS simulations, dramatically change TERS images. This calls for the inclusion of chemical effects for predictive theory-experiment comparisons and understanding of molecular motion at the nanoscale.

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Language(s): -
 Dates: 2022-11-17
 Publication Status: Published online
 Pages: 32
 Publishing info: -
 Table of Contents: -
 Rev. Type: No review
 Identifiers: arXiv: 2211.09475
 Degree: -

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