Issue 24, 2021, Issue in Progress

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

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%.

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

Article information

Article type
Paper
Submitted
15 Mar 2021
Accepted
01 Apr 2021
First published
19 Apr 2021
This article is Open Access
Creative Commons BY license

RSC Adv., 2021,11, 14552-14561

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

X. Liu, G. Meijer and J. Pérez-Ríos, RSC Adv., 2021, 11, 14552 DOI: 10.1039/D1RA02061G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements