Researchers from the University of Tennessee, Knoxville, including Shahzad Akram, Sutirtha Paul, Collin Kovacs, Vasileios Maroulas, Adrian Del Maestro, and Konstantinos D. Vogiatzis, have recently published a study in the Journal of Chemical Physics that delves into the intricate world of non-covalent interactions between helium and graphitic materials. Their work focuses on creating an accurate potential energy surface (PES) for the helium-benzene complex, a fundamental prototype for understanding quantum phenomena in reduced dimensions.
The team employed a multi-level investigation approach, starting with high-level coupled-cluster singles-and-doubles with perturbative triples (CCSD(T)) methods to establish benchmark energies. They then extrapolated these energies to the complete basis set limit and assessed higher-order contributions using CCSDT(Q). To gain deeper insights, they used symmetry-adapted perturbation theory (SAPT) to benchmark against CCSD(T) and decompose the interaction into its physical components. They found that the interaction is primarily a balance between dispersion and exchange-repulsion.
To construct a continuous, three-dimensional PES from discrete ab initio points, the researchers utilized multifidelity Gaussian process regression. This method combines density functional theory results with sparse coupled-cluster energies, resulting in a highly accurate PES with sub-cm-1 accuracy that adheres to physical laws.
The new PES was then applied to path integral Monte Carlo (PIMC) simulations to study the solvation of helium atoms on benzene at low temperatures. The PIMC results revealed qualitatively different solvation behavior, particularly in the filling of adsorption layers, compared to simulations using commonly employed empirical Lennard-Jones potentials.
This research provides a benchmark PES that is essential for accurate many-body simulations of helium on larger polycyclic aromatic hydrocarbons, paving the way for better understanding and potential applications in the energy sector. For instance, the insights gained from this study could contribute to the development of more efficient adsorption-based technologies for helium separation and purification, which are crucial for various energy applications, including nuclear power and medical imaging.
The study, titled “Accurate Helium-Benzene Potential: from CCSD(T) to Gaussian Process Regression,” was published in the Journal of Chemical Physics.
This article is based on research available at arXiv.