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

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.

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

Potential-Energy Surfaces Using Expansion Methods and Neural Networks

2012 ◽  
Author(s):  
Lionel Raff ◽  
Ranga Komanduri ◽  
Martin Hagan ◽  
Satish Bukkapatnam
Keyword(s):  
Neural Networks ◽  
Potential Energy ◽  
Basic Concept ◽  
Potential Energy Surfaces ◽  
Expansion Method ◽  
Focus Of Attention ◽  
Molecular Systems ◽  
Internal Coordinates ◽  
Energy Surfaces ◽  
Atom System

Expansion methods have been employed for some time to represent the potentialenergy surface for molecular systems. The basic concept involved with any expansion method is to write the PES expression for an N-atom system that requires the specification of 3N-6 internal coordinates as a sum of terms each of which involves fewer than N atoms and/or fewer than (3N-6) coordinate variables. Two approaches to the implementation of this concept have been suggested. In the first approach, the focus of attention is the number of internal coordinates upon which each term in the expansion depends.

Development of generalized potential-energy surfaces using many-body expansions, neural networks, and moiety energy approximations

2009 ◽  
Vol 130 (18) ◽  
pp. 184102 ◽  
Author(s):  
M. Malshe ◽  
R. Narulkar ◽  
L. M. Raff ◽  
M. Hagan ◽  
S. Bukkapatnam ◽  
...  
Keyword(s):  
Neural Networks ◽  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Many Body ◽  
Generalized Potential ◽  
Energy Surfaces
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