Potential Energy Surfaces Fitted by Artificial Neural Networks

2010 ◽  
Vol 114 (10) ◽  
pp. 3371-3383 ◽  
Author(s):  
Chris M. Handley ◽  
Paul L. A. Popelier
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Artificial Neural ◽  
Energy Surfaces

scholarly journals Representation of coupled adiabatic potential energy surfaces using neural network based quasi-diabatic Hamiltonians: 1,2 2A′ states of LiFH

2019 ◽  
Vol 21 (26) ◽  
pp. 14205-14213 ◽  
Author(s):  
Yafu Guan ◽  
Dong H. Zhang ◽  
Hua Guo ◽  
David R. Yarkony
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Adiabatic Potential ◽  
General Algorithm ◽  
Energy Surfaces

A general algorithm for determining diabatic representations from adiabatic energies, energy gradients and derivative couplings using neural networks is introduced.

Approach to potential energy surfaces by neural networks. A review of recent work

2009 ◽  
Vol 110 (2) ◽  
pp. 432-445 ◽  
Author(s):  
Diogo A. R. S. Latino ◽  
Rui P. S. Fartaria ◽  
Filomena F. M. Freitas ◽  
João Aires-De-Sousa ◽  
Fernando M. S. Silva Fernandes
Keyword(s):  
Neural Networks ◽  
Potential Energy ◽  
Recent Work ◽  
Potential Energy Surfaces ◽  
Energy Surfaces

Neural networks to approach potential energy surfaces: Application to a molecular dynamics simulation

2007 ◽  
Vol 107 (11) ◽  
pp. 2120-2132 ◽  
Author(s):  
Diogo A. R. S. Latino ◽  
Filomena F. M. Freitas ◽  
João Aires-De-Sousa ◽  
Fernando M. S. Silva Fernandes
Keyword(s):  
Neural Networks ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Dynamics Simulation ◽  
Energy Surfaces
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