The potential energy surface and vibrational structure of C3H−

2001 ◽  
Vol 115 (8) ◽  
pp. 3664-3672 ◽  
Author(s):  
Nicholas M. Lakin ◽  
Majdi Hochlaf ◽  
Gilberte Chambaud ◽  
Pavel Rosmus
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Vibrational Structure

scholarly journals Ab Initio Ro-Vibrational Structure of the C2? Isotopes of H2O+

1992 ◽  
Vol 45 (5) ◽  
pp. 651 ◽  
Author(s):  
F Wang ◽  
EI von Nagy-Felsobuki
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Force Field ◽  
Ab Initio ◽  
Excellent Agreement ◽  
Energy Surface ◽  
Variational Calculation ◽  
Vibrational Structure ◽  
Vibrational States ◽  
Normal Coordinate

The ro-vibrational structures of the C2" isotopes ofH20+ have been calculated from variational solution of the normal coordinate Eckart-Watson Hamiltonian. The calculations use the discrete ab initio potential energy surface of Weis et al. (1989). Where comparisons can be made, the assignment of the vibrational states is in excellent agreement with experiment and with the ab initio variational calculation of Weis et al., who utilised a different force field and an internal coordinate nuclear Hamiltonian (instead of the Eckart-Watson amiltonian). Furthermore, the calculated rotational levels of the ground and the first excited vibrational states of H20+ and D20+ are in excellent agreement with experiment.

Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces

2020 ◽  
Author(s):  
Shi Jun Ang ◽  
Wujie Wang ◽  
Daniel Schwalbe-Koda ◽  
Simon Axelrod ◽  
Rafael Gomez-Bombarelli
Keyword(s):  
Molecular Dynamics ◽  
Potential Energy ◽  
Transition State ◽  
Potential Energy Surface ◽  
Ab Initio ◽  
Energy Surface ◽  
Computational Cost ◽  
Reactive Trajectories ◽  
Dynamics Simulations ◽  
Energy Surfaces

<div>Modeling dynamical effects in chemical reactions, such as post-transition state bifurcation, requires <i>ab initio</i> molecular dynamics simulations due to the breakdown of simpler static models like transition state theory. However, these simulations tend to be restricted to lower-accuracy electronic structure methods and scarce sampling because of their high computational cost. Here, we report the use of statistical learning to accelerate reactive molecular dynamics simulations by combining high-throughput ab initio calculations, graph-convolution interatomic potentials and active learning. This pipeline was demonstrated on an ambimodal trispericyclic reaction involving 8,8-dicyanoheptafulvene and 6,6-dimethylfulvene. With a dataset size of approximately</div><div>31,000 M062X/def2-SVP quantum mechanical calculations, the computational cost of exploring the reactive potential energy surface was reduced by an order of magnitude. Thousands of virtually costless picosecond-long reactive trajectories suggest that post-transition state bifurcation plays a minor role for the reaction in vacuum. Furthermore, a transfer-learning strategy effectively upgraded the potential energy surface to higher</div><div>levels of theory ((SMD-)M06-2X/def2-TZVPD in vacuum and three other solvents, as well as the more accurate DLPNO-DSD-PBEP86 D3BJ/def2-TZVPD) using about 10% additional calculations for each surface. Since the larger basis set and the dynamic correlation capture intramolecular non-covalent interactions more accurately, they uncover longer lifetimes for the charge-separated intermediate on the more accurate potential energy surfaces. The character of the intermediate switches from entropic to thermodynamic upon including implicit solvation effects, with lifetimes increasing with solvent polarity. Analysis of 2,000 reactive trajectories on the chloroform PES shows a qualitative agreement with the experimentally-reported periselectivity for this reaction. This overall approach is broadly applicable and opens a door to the study of dynamical effects in larger, previously-intractable reactive systems.</div>

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