Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks

2005 ◽  
Vol 122 (8) ◽  
pp. 084104 ◽  
Author(s):  
L. M. Raff ◽  
M. Malshe ◽  
M. Hagan ◽  
D. I. Doughan ◽  
M. G. Rockley ◽  
...  
Keyword(s):  
Neural Networks ◽  
Potential Energy ◽  
Ab Initio ◽  
Potential Energy Surfaces ◽  
Feedforward Neural Networks ◽  
Multichannel Systems ◽  
Energy Surfaces

scholarly journals Raman spectrum and polarizability of liquid water from deep neural networks

2020 ◽  
Vol 22 (19) ◽  
pp. 10592-10602 ◽  
Author(s):  
Grace M. Sommers ◽  
Marcos F. Calegari Andrade ◽  
Linfeng Zhang ◽  
Han Wang ◽  
Roberto Car
Keyword(s):  
Neural Networks ◽  
Molecular Dynamics ◽  
Raman Spectrum ◽  
Potential Energy ◽  
Ab Initio ◽  
Liquid Water ◽  
Potential Energy Surfaces ◽  
Deep Neural Networks ◽  
Energy Surfaces

Using deep neural networks to model the polarizability and potential energy surfaces, we compute the Raman spectrum of liquid water at several temperatures with ab initio molecular dynamics accuracy.

Neural networks as a tool for compact representation of ab initio molecular potential energy surfaces

1996 ◽  
Vol 14 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Erwin Tafeit ◽  
Willibald Estelberger ◽  
Renate Horejsi ◽  
Reinhard Moeller ◽  
Karl Oettl ◽  
...  
Keyword(s):  
Neural Networks ◽  
Potential Energy ◽  
Ab Initio ◽  
Potential Energy Surfaces ◽  
Compact Representation ◽  
Molecular Potential ◽  
Molecular Potential Energy ◽  
Energy Surfaces

scholarly journals Global ab initio potential energy surfaces for the O2(Σ3g−)+O2(Σ3g−) interaction

2010 ◽  
Vol 133 (12) ◽  
pp. 124311 ◽  
Author(s):  
Massimiliano Bartolomei ◽  
Estela Carmona-Novillo ◽  
Marta I. Hernández ◽  
José Campos-Martínez ◽  
Ramón Hernández-Lamoneda
Keyword(s):  
Potential Energy ◽  
Ab Initio ◽  
Potential Energy Surfaces ◽  
Energy Surfaces

Intermolecular potential energy surfaces and spectra of Ne–HCN complex from ab initio calculations

2001 ◽  
Vol 114 (2) ◽  
pp. 764 ◽  
Author(s):  
Garold Murdachaew ◽  
Alston J. Misquitta ◽  
Robert Bukowski ◽  
Krzysztof Szalewicz
Keyword(s):  
Potential Energy ◽  
Ab Initio Calculations ◽  
Ab Initio ◽  
Potential Energy Surfaces ◽  
Intermolecular Potential ◽  
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.

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