A data-driven approach to determine dipole moments of diatomic molecules.

Xiangyue Liu,Jesús Pérez-Ríos,Gerard Meijer

doi:10.1039/d0cp03810e

Abstract

We present a data-driven approach for the prediction of the electric dipole moment of diatomic molecules, which is one of the most relevant molecular properties. In particular, we apply Gaussian process regression to a novel dataset to show that dipole moments of diatomic molecules can be learned, and hence predicted, with a relative error ⪅5%. The dataset contains the dipole moment of 162 diatomic molecules, the most exhaustive and unbiased dataset of dipole moments up to date. Our findings show that the dipole moment of diatomic molecules depends on atomic properties of the constituents atoms: electron affinity and ionization potential, as well as on (a feature related to) the first derivative of the electronic kinetic energy at the equilibrium distance.

Highlights

The study of relationships between spectroscopic constants is a traditional topic in chemical physics since the pioneering work of Kratzer and Mecke, among others[1,2,3,4,5,6] and is beautifully summarized by Varshini.[7,8] Recently, we have shown that some spectroscopic constants are universally related,[9] i.e., the relationships between them are independent of the nature of the molecular bond
Our findings show that the dipole moment of diatomic molecules depends on atomic properties of the constituents atoms: electron affinity and ionization potential, as well as on the first derivative of the electronic kinetic energy at the equilibrium distance
We have shown that through a Gaussian process regression (GPR) model, the ground state dipole moments of diatomic molecules can be related to spectroscopic constants, namely Re and oe

Summary

Introduction

The study of relationships between spectroscopic constants is a traditional topic in chemical physics since the pioneering work of Kratzer and Mecke, among others[1,2,3,4,5,6] and is beautifully summarized by Varshini.[7,8] Recently, we have shown that some spectroscopic constants are universally related,[9] i.e., the relationships between them are independent of the nature of the molecular bond. The electric dipole moment of a molecule, despite being an essential molecular property, has not been considered in previous studies about relationships between spectroscopic constants. There have been some efforts towards the understanding of the dipole moment in terms of molecular spectroscopic constants. As a result, it has been found by Hou and Bernath that the expression for the dipole moment, d, taught in elementary chemistry courses d = qRe,. Our results reveal that it is not possible to predict the dipole moment of a molecule solely from atomic properties, this is feasible for the spectroscopic constants,[9] but that it is necessary to include molecular features. The molecular spectroscopic constants are needed in a combination that describes the force on the electrons at the equilibrium distance, i.e., in a combination that has the same functional dependence as the first derivative of the electronic kinetic energy at the equilibrium distance

An overview on the nature of the electric dipole moment of molecules

Gaussian process regression

Model evaluation

The dataset

Results and discussion

Conclusions