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

A neural network/trajectory approach is presented for the development of accurate potential-energy hypersurfaces that can be utilized to conduct ab initio molecular dynamics (AIMD) and Monte Carlo studies of gas-phase chemical reactions, nanometric cutting, and nanotribology, and of a variety of mec...

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Veröffentlicht in:	The Journal of chemical physics 2005-02, Vol.122 (8), p.84104-84104
Hauptverfasser:	Raff, L M, Malshe, M, Hagan, M, Doughan, D I, Rockley, M G, Komanduri, R
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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