The Reaction: Thermal and Vibrational Relaxation Rates for the A, A and A States
arXiv:1911.04792 · doi:10.1039/C9CP06085E
Abstract
The kinetics and vibrational relaxation of the reaction is investigated over a wide temperature range based on quasiclassical trajectory simulations on 3-dimensional potential energy surfaces (PESs) for the lowest three electronic states. Reference energies at the multi reference configuration interaction level are represented as a reproducing kernel and the topology of the PESs is rationalized by analyzing the CASSCF wavefunction of the relevant states. The forward rate matches one measurement at 1575 K and is somewhat lower than the high-temperature measurement at 2880 K whereas for the reverse rate the computations are in good agreement for temperatures between 3000 and 4100 K. The temperature-dependent equilibrium rates are consistent with results from JANAF and CEA results. Vibrational relaxation rates for O + NO() O + NO() are consistent with a wide range of experiments. This process is dominated by the dynamics on the A and A surfaces which both contribute similarly up to temperatures K, and it is found that vibrationally relaxing and non-relaxing trajectories probe different parts of the potential energy surface. The total cross section depending on the final vibrational state monotonically decreases which is consistent with early experiments and previous simulations but at variance with other recent experiments which reported an oscillatory cross section.
Cited by in corpus (14)
- Neural Network Potentials for Chemistry: Concepts, Applications and Prospects
- Permutationally Invariant, Reproducing Kernel-Based Potential Energy Surfaces for Polyatomic Molecules: From Formaldehyde to Acetone
- Accurate Reproducing Kernel-Based Potential Energy Surfaces for the Triplet Ground States of NO and Dynamics for the N+NOO+N and N+O2N+O Reactions
- ML Models of Vibrating HCO: Comparing Reproducing Kernels, FCHL and PhysNet
- Perspective: Non-conventional Force Fields for Applications in Spectroscopy and Chemical Reaction Dynamics
- Machine Learning Product State Distributions from Initial Reactant States for a Reactive Atom-Diatom Collision System
- Dynamics on Multiple Potential Energy Surfaces: Quantitative Studies of Elementary Processes Relevant to Hypersonics
- Machine Learning for Observables: Reactant to Product State Distributions for Atom-Diatom Collisions
- Thermal Activation of Methane by MgO: Temperature Dependent Kinetics, Reactive Molecular Dynamics Simulations and Statistical Modeling
- Combining Machine Learning and Spectroscopy to Model Reactive Atom + Diatom Collisions
- Low-Temperature Kinetics for the N + NO reaction: Experiment Guides the Way
- N: Full-Dimensional Potential Energy Surface, Vibrational Energy Levels and Ground State Dynamics
- Photodissociation dynamics of N
- Quantitative Molecular Simulations