title: Full-dimensional global potential energy surfaces describing abstraction and exchange for the H + H2S reaction.
abstract: For the H + H2S system, ∼34 000 data points are sampled over a large configuration space including both abstraction and exchange channels, and calculated at the level of explicitly correlated unrestricted coupled cluster method with singles, doubles, and perturbative triples excitations with the augmented correlation-consistent polarized triple zeta basis set (UCCSD(T)-F12a/aug-cc-pVTZ). The data set was fit using the newly proposed permutation invariant polynomial-neural network (PIP-NN) method with three different vectors as the input: two redundant sets of PIPs, one with the maximum order four (PES-I) and one with the maximum order three (PES-II), and nine non-redundant PIPs (PES-III). All these PESs show small fitting errors and essentially the same performance in representing the title system. Various kinetics and dynamical properties are calculated using the tunneling corrected transition state theory and quasi-classical trajectory, and compared with available experimental results. At a collision energy of 10 kcal/mol, both the H2 and SH products are found to be internally cold, with ∼20% of H2 at its first vibrational excited state, while SH is essentially a spectator. The angular distributions of the products are mainly in backward with considerable contributions from sideway direction. In addition, analytical partial derivatives of any PIP-NN PES with respect to the coordinates of atoms are derived by making use of the monomial symmetrization algorithm [Z. Xie and J. M. Bowman, J. Chem. Theory Comput. 6, 26-34 (2010)]. It can not only accelerate the evaluation of the derivatives, but also improve the energy convergence significantly.
authors.affiliation: School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 401331, China.
authors.forename: Dandan
authors.initials: D
authors.lastname: Lu
authors.affiliation: School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 401331, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Li