Infrared Spectroscopy of Protonated Water Clusters via the Quantum Thermal Bath Method and Highly Accurate...

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Spectroscopy

Background:

• Spectral features of water clusters reveal crucial insights into their structure, dynamics, and the local environment of aqueous solutions.
• Accurate numerical simulations of these features are challenging, often requiring sophisticated electronic structure methods and expensive quantum dynamics techniques.

Purpose of the Study:

• To develop and present a more cost-effective yet accurate computational approach for simulating the infrared (IR) spectra of protonated water clusters.
• To evaluate the performance of machine-learned potential energy and dipole moment surfaces combined with the quantum thermal bath (QTB) methodology.

Main Methods:

• Employed molecular dynamics simulations utilizing highly accurate machine-learned potential energy surfaces (PES) and dipole moment surfaces (DMS).
• Integrated the quantum thermal bath (QTB) methodology to efficiently incorporate nuclear quantum effects (NQEs) into the simulations.
• Simulated IR spectra for protonated water clusters from monomer to tetramer.

Main Results:

• The combined PES, DMS, and QTB approach yielded accurate IR spectra for protonated water clusters.
• This method demonstrated comparable accuracy to more computationally intensive techniques like ring polymer molecular dynamics (RPMD).
• The simulations provided a significantly cheaper alternative for calculating these spectral features.

Conclusions:

• The combination of machine-learned surfaces and QTB offers a computationally efficient and accurate method for simulating IR spectra of water clusters.
• This approach facilitates the study of aqueous solution environments under various conditions.
• It presents a viable and cost-effective alternative to traditional high-level quantum dynamics methods.