Constructing high-accuracy intermolecular potential energy surface with multi-dimension Morse/Long-Range model

ABSTRACT

Spectroscopically accurate Potential Energy Surfaces (PESs) are fundamental for explaining and making predictions of the infrared and microwave spectra of van der Waals (vdW) complexes, and the model used for the potential energy function is critically important for providing accurate, robust and portable analytical PESs. The Morse/Long-Range (MLR) model has proved to be one of the most general, flexible and accurate one-dimensional (1D) model potentials, as it has physically meaningful parameters, is flexible, smooth and differentiable everywhere, to all orders and extrapolates sensibly at both long and short ranges. The Multi-Dimensional Morse/Long-Range (mdMLR) potential energy model described herein is based on that 1D MLR model, and has proved to be effective and accurate in the potentiology of various types of vdW complexes. In this paper, we review the current status of development of the mdMLR model and its application to vdW complexes. The future of the mdMLR model is also discussed. This review can serve as a tutorial for the construction of an mdMLR PES.

KEYWORDS:

• van der Waals complexes
• potential energy surfaces
• potential energy model
• potentiology

Acknowledgments

Yu Zhai and Hui Li thank Prof. Jiali Gao (Jilin University) and Prof. Pierre-Nicholas Roy (University of Waterloo) for inspiring discussion. This review has been supported by the National Key Research and Development Program (No. 2017YFB0203401 and 2016YFB0700801) and the National Natural Science Foundation of China (Grant No. 21773081, 21533003 and 91541124), and by the Natural Sciences and Engineering Research Council of Canada through a Discovery Grant (NSERC-RGPIN-03929-2014) to Robert J. Le Roy.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

National Natural Science Foundation of China [grant number 21773081], [grant number 21533003], [grant number 91541124]; National Key Research and Development Program [grant number 2017YFB0203401], [grant number 2016YFB0700801]; Natural Sciences and Engineering Research Council of Canada[NSERC-RGPIN-03929-2014].