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  On the relationship between spectroscopic constants of diatomic molecules: a machine learning approach

Liu, X., Meijer, G., & Pérez-Ríos, J. (2021). On the relationship between spectroscopic constants of diatomic molecules: a machine learning approach. RSC Advances, 11(24), 14552-14561. doi:10.1039/D1RA02061G.

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 Creators:
Liu, Xiangyue1, Author           
Meijer, Gerard1, Author           
Pérez-Ríos, Jesús1, Author           
Affiliations:
1Molecular Physics, Fritz Haber Institute, Max Planck Society, ou_634545              

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 Abstract: Through a machine learning approach, we show that the equilibrium distance, harmonic vibrational frequency and binding energy of diatomic molecules are related, independently of the nature of the bond of a molecule; they depend solely on the group and period of the constituent atoms. As a result, we show that by employing the group and period of the atoms that form a molecule, the spectroscopic constants are predicted with an accuracy of <5%, whereas for the A-excited electronic state it is needed to include other atomic properties leading to an accuracy of <11%.

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Language(s): eng - English
 Dates: 2021-03-152021-04-012021-04-19
 Publication Status: Published online
 Pages: 10
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1039/D1RA02061G
 Degree: -

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Title: RSC Advances
  Abbreviation : RSC Adv.
Source Genre: Journal
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Publ. Info: Cambridge, UK : Royal Society of Chemistry
Pages: 10 Volume / Issue: 11 (24) Sequence Number: - Start / End Page: 14552 - 14561 Identifier: ISSN: 2046-2069
CoNE: https://pure.mpg.de/cone/journals/resource/2046-2069