Semiclassical Multistate Dynamics for Six Coupled 5 A ' States of O + O 2 .
Farideh Badichi AkherYinan ShuZoltan VargaDonald G TruhlarPublished in: Journal of chemical theory and computation (2023)
Dynamics simulations of high-energy O 2 -O collisions play an important role in simulating thermal energy content and heat flux in flows around hypersonic vehicles. To carry out such dynamics simulations efficiently requires accurate global potential energy surfaces and (in most algorithms) state couplings for many energetically accessible electronic states. The ability to treat collisions involving many coupled electronic states has been a challenge for decades. Very recently, a new diabatization method, the parametrically managed diabatization by deep neural network (PM-DDNN), has been developed. The PM-DDNN method uses a deep neural network architecture with an activation function parametrically dependent on input data to discover and fit the diabatic potential energy matrix (DPEM) as a function of geometry, and the adiabatic potential energy surfaces are obtained by diagonalization of a small matrix with analytic matrix elements. Here, we applied the PM-DDNN method to the six lowest-energy potential energy surfaces in the 5 A ' manifold of O 3 to perform simultaneous diabatization and fitting; the data are obtained by extended multistate complete-active-space second-order perturbation theory. We then used the adiabatic surfaces for dynamics calculations with three methods: coherent switching with decay of mixing (CSDM), curvature-driven CSDM (κCSDM), and electronically curvature-driven CSDM (eκCSDM). The κCSDM calculations require only adiabatic potential energies and gradients. The three dynamical methods are in good agreement. We then calculated electronically nonadiabatic, electronically inelastic, and dissociative cross sections for seven initial collision energies, five initial vibrational levels, and four initial rotational levels. Trends in the electronically inelastic cross sections as functions of the initial collision energy and vibrational level were rationalized in terms of the coordinate ranges where the gaps between the second and third potential energy surfaces are small.
Keyphrases
- density functional theory
- neural network
- molecular dynamics
- biofilm formation
- molecular dynamics simulations
- air pollution
- particulate matter
- human health
- machine learning
- pseudomonas aeruginosa
- staphylococcus aureus
- high resolution
- electronic health record
- deep learning
- risk assessment
- polycyclic aromatic hydrocarbons
- quantum dots