A ground state potential energy surface for HONO based on a neural network with exponential fitting functions

Ekadashi Pradhan, Alex Brown

Physical Chemistry Chemical Physics · 2017 · 43 citations · 101 references

Concepts

Abstract

above the energy minimum. The PESs are validated by computing vibrational energies using block improved relaxation with the multi configuration time dependent Hartree (MCTDH) approach. The vibrational frequencies obtained on the PESs are compared to available experimental measurements, previous theoretical computations based on a CCSD(T)/cc-pVQZ(-g functions) PES, and anharmonic frequencies at the MP2/aug-cc-pVTZ and CCSD(T)/aug-cc-pVTZ levels of theory obtained using second-order vibrational perturbation theory. The results suggest that these are the best available PESs for HONO, and thus, should be suitable for a variety of dynamics studies, including quantum dynamics with MCTDH where the sum-of-products form can be exploited for computational efficiency.

References

101