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  Fully First-Principles Surface Spectroscopy with Machine Learning

Litman, Y., Lan, J., Nagata, Y., & Wilkins, D. M. (2023). Fully First-Principles Surface Spectroscopy with Machine Learning. The Journal of Physical Chemistry Letters, 14(36), 8175-8182. doi:10.1021/acs.jpclett.3c01989.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-BCC8-E Version Permalink: https://hdl.handle.net/21.11116/0000-000D-BCC9-D
Genre: Journal Article

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2023-09-26-acs.jpclett.3c01989.pdf (Publisher version), 2MB
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2023-09-26-acs.jpclett.3c01989.pdf
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Copyright Date:
2022
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https://creativecommons.org/licenses/by/4.0/

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 Creators:
Litman, Yair1, 2, Author           
Lan, Jinggang, Author
Nagata, Yuki1, Author           
Wilkins, David M., Author
Affiliations:
1Dept. Bonn: Molecular Spectroscopy, MPI for Polymer Research, Max Planck Society, ou_1800285              
2University of Cambridge, Cambridge, United Kingdom, ou_persistent22              

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Language(s): eng - English
 Dates: 2023-09-06
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1021/acs.jpclett.3c01989
 Degree: -

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Project name : MaxWater Initiative by the Max Planck Society
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Funding organization : Max Planck Society

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Title: The Journal of Physical Chemistry Letters
  Abbreviation : J. Phys. Chem. Lett.
Source Genre: Journal
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Publ. Info: Washington, DC : American Chemical Society
Pages: - Volume / Issue: 14 (36) Sequence Number: - Start / End Page: 8175 - 8182 Identifier: ISSN: 1948-7185
CoNE: https://pure.mpg.de/cone/journals/resource/1948-7185