Critical role of quantum dynamical effects in the Raman spectroscopy of liquid water

ABSTRACT

Understanding the Raman spectroscopy at the atomistic level is important for the elucidation of dynamical processes in liquid water. Because the polarisability (or its time derivative) is often a highly nonlinear function of coordinates or/and momenta, we employ the linearized semiclassical initial value representation for quantum dynamical simulations of liquid water (and heavy water) under ambient conditions based on an ab initio-based, flexible, polarisable model (the POLI2VS force field). It is shown that quantum dynamical effects play a critical role in reproducing the peaks in the intermediate region between the librational and bending bands, those between the bending and stretching bands, and the double-peak in the stretching band in the experimental isotropic Raman spectrum. In contrast, quantum dynamical effects are important but less decisive in the anisotropic Raman spectrum. By selectively freezing either the intramolecular O–H stretching or H–O–H bending mode, we demonstrate that the peak in the intermediate region (2000–2400 cm⁻¹) of the isotropic Raman spectrum arises from the interplay of the stretching and bending motions while a substantial part of the peak in the same intermediate region of the anisotropic Raman spectrum may be attributed to the combined motion of the bending and librational modes.

KEYWORDS:

• Raman Spectroscopy
• nuclear quantum effects
• quantum dynamics
• correlation functions
• intermediate regions

Acknowledgments

We thank Taisuke Hasegawa and Yoshitaka Tanimura for sending us the code for their POLI2VS water force field. This work was supported by the Ministry of Science and Technology of China (MOST) Grants No. 2016YFC0202803 and No. 2017YFA0204901, by the National Natural Science Foundation of China (NSFC) Grants No. 21373018 and No. 21573007, by the Recruitment Program of Global Experts, by Specialized Research Fund for the Doctoral Program of Higher Education No. 20130001110009, and by Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase) under grant number U1501501. We acknowledge the Beijing and Tianjin supercomputer centers and the High-performance Computing Platform of Peking University for providing computational resources. This research also used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Ministry of Science and Technology of the People’s Republic of China (MOST) [grant number 2016YFC0202803], [grant number 2017YFA0204901]; National Natural Science Foundation of China (NSFC) [grant number 21373018], [grant number 21573007].