A benchmark ab initio study of the complex potential energy surfaces of the OH− + CH3CH2Y [Y = F, Cl, Br, I] reactions

Ab Initio Study ◽

Explicitly Correlated ◽

High Level ◽

We provide the first benchmark characterization of the OH− + CH3CH2Y [Y = F, Cl, Br, I] reactions utilizing the high-level explicitly-correlated CCSD(T)-F12b method with the aug-cc-pVnZ [n = 2(D),...

Benchmark ab Initio Characterization of the Complex Potential Energy Surfaces of the X– + NH2Y [X, Y = F, Cl, Br, I] Reactions

The Journal of Physical Chemistry A ◽

10.1021/acs.jpca.7b11927 ◽

2018 ◽

Vol 122 (7) ◽

pp. 1886-1895 ◽

Cited By ~ 6

Author(s):

Bálint Hajdu ◽

Gábor Czakó

Keyword(s):

Potential Energy ◽

Ab Initio ◽

Complex Potential ◽

The spin-forbidden reaction CH( 2 ∏) + N 2 → HCN + N( 4 S) revisited I. Ab initio study of the potential energy surfaces

Theoretical Chemistry Accounts ◽

10.1007/s002140050482 ◽

1999 ◽

Vol 102 (1-6) ◽

pp. 127-133 ◽

Cited By ~ 20

Author(s):

Qiang Cui ◽

Keiji Morokuma

Keyword(s):

Potential Energy ◽

Ab Initio ◽

Ab Initio Study ◽

Characterization of intermediates on the 1O2 + R2S potential energy surface. A high-level ab initio study

Journal of Molecular Structure THEOCHEM ◽

10.1016/s0166-1280(97)00085-7 ◽

1998 ◽

Vol 422 (1-3) ◽

pp. 123-132 ◽

Cited By ~ 6

Author(s):

Christine Shangguan ◽

Michael A. McAllister

Keyword(s):

Potential Energy ◽

Potential Energy Surface ◽

Ab Initio ◽

Energy Surface ◽

Ab Initio Study ◽

High Level

Ab Initio Study of the Potential Energy Surfaces for the Reaction C + CH → C2+ H

The Journal of Physical Chemistry A ◽

10.1021/jp9726596 ◽

1998 ◽

Vol 102 (11) ◽

pp. 2009-2015 ◽

Cited By ~ 20

Author(s):

M. Boggio-Pasqua ◽

Ph. Halvick ◽

M.-T. Rayez ◽

J.-C. Rayez ◽

J.-M. Robbe

Keyword(s):

Potential Energy ◽

Ab Initio ◽

Ab Initio Study ◽

The lowest doublet and quartet potential energy surfaces involved in the N(4S)+O2 reaction. I. Ab initio study of the Cs-symmetry (2A′, 4A′) abstraction and insertion mechanisms

The Journal of Chemical Physics ◽

10.1063/1.1381012 ◽

2001 ◽

Vol 115 (3) ◽

pp. 1287-1297 ◽

Cited By ~ 16

Author(s):

R. Sayós ◽

Carolina Oliva ◽

Miguel González

Keyword(s):

Potential Energy ◽

Ab Initio ◽

Ab Initio Study ◽

Fitting potential energy surfaces to sum-of-products form with neural networks using exponential neurons

Journal of Theoretical and Computational Chemistry ◽

10.1142/s0219633617300014 ◽

2017 ◽

Vol 16 (05) ◽

pp. 1730001 ◽

Cited By ~ 6

Author(s):

Alex Brown ◽

E. Pradhan

Keyword(s):

Neural Network ◽

Potential Energy ◽

Ab Initio ◽

Quantum Dynamics ◽

The Neural Network ◽

Sum Of Products ◽

High Level ◽

Energy Surfaces ◽

Dynamics Problems

In this paper, the use of the neural network (NN) method with exponential neurons for directly fitting ab initio data to generate potential energy surfaces (PESs) in sum-of-product form will be discussed. The utility of the approach will be highlighted using fits of CS2, HFCO, and HONO ground state PESs based upon high-level ab initio data. Using a generic interface between the neural network PES fitting, which is performed in MATLAB, and the Heidelberg multi-configuration time-dependent Hartree (MCTDH) software package, the PESs have been tested via comparison of vibrational energies to experimental measurements. The review demonstrates the potential of the PES fitting method, combined with MCTDH, to tackle high-dimensional quantum dynamics problems.