The quasi-classical trajectory predicts the rate coefficient of the OH + HO2 → H2O + O2 reaction based on a full dimensional accurate PIP-NN PES, which is fit to 108 000 points calculated at the CCSD(T)-F12a/AVTZ level.
The interaction between HCl and H2O is of considerable theoretical and experimental interest due to its important role in atmospheric chemistry and understanding the onset of the dissociation of HCl...
A reaction
typically involves a few active modes while the other
modes are largely preserved throughout the reaction as spectators.
Excitation of an active mode is expected to promote the reaction,
but depositing energy in a spectator mode typically has no effect,
because of the differing ability for energy flow to the reaction coordinate.
In this work, we report a surprising case of mode specificity in a
key radical–radical reaction OH + HO2 → H2O + O2, where such canonical expectations fail
to hold. Despite its spectator nature, the vibrational excitation
of the OH reactant is shown at low collision energies to enhance the
reactivity significantly. This unique effect can be attributed to
the increased attraction with HO2 due to the larger dipole
of the stretched OH. At low collision energies, the stronger attraction
increases the chance of capturing the reactants to form a hydrogen-bonded
complex, thus of passing through the submerged barrier. The novel
mechanism differs from the conventional vibrational enhancement via
coupling to the reaction coordinate at the transition state, enriching
our understanding of mode specificity in chemistry.
Δ-machine
learning, or the hierarchical construction scheme,
is a highly cost-effective method, as only a small number of high-level ab initio energies are required to improve a potential energy
surface (PES) fit to a large number of low-level points. However,
there is no efficient and systematic way to select as few points as
possible from the low-level data set. We here propose a permutation-invariant-polynomial
neural-network (PIP-NN)-based Δ-machine learning approach to
construct full-dimensional accurate PESs of complicated reactions
efficiently. Particularly, the high flexibility of the NN is exploited
to efficiently sample points from the low-level data set. This approach
is applied to the challenging case of a HO2 self-reaction
with a large configuration space. Only 14% of the DFT data set is
used to successfully bring a newly fitted DFT PES to the UCCSD(T)-F12a/AVTZ
quality. Then, the quasiclassical trajectory (QCT) calculations are
performed to study its dynamics, particularly the mode specificity.
Thermal rate coefficients for the Cl + CH4/CD4 reactions were studied on a new full-dimensional accurate potential energy surface with the spin–orbit corrections considered in the entrance channel.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.