Potential energy surfaces for macromolecules. A neural network technique

Bobby G. Sumpter; Donald W. Noid

doi:10.1016/0009-2614(92)85498-Y

Potential energy surfaces for macromolecules. A neural network technique

Bobby G. Sumpter, Donald W. Noid

Center for Nanophase Matls Sciences

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Abstract

A method for obtaining potential energy surfaces for macromolecules is described. The basis of the method is the use of a neural network to learn the relationship between vibrational spectra and a multidimensional potential energy surface (PES). The results demonstrate that the neural network is capable of mapping the vibrational motion determined from spectra onto a fully coupled PES with relatively high levels of accuracy.

Original language	English
Pages (from-to)	455-462
Number of pages	8
Journal	Chemical Physics Letters
Volume	192
Issue number	5-6
DOIs	https://doi.org/10.1016/0009-2614(92)85498-Y
State	Published - May 15 1992

Funding

This work was supported by the Division of Materials Sciences, Office of Basic Energy Sciences, US Department of Energy, under Contract No. DE-AC05-840R21400 with Martin Marietta Energy Systems, Inc., and by the Polymer Program of the National Science Foundation, present Grant No. DMR-8818412. The computations were performed on the IBM-3090 at the University of Tennessee and the GRAY-XMP/14 at Oak Ridge National Laboratory.

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abstract = "A method for obtaining potential energy surfaces for macromolecules is described. The basis of the method is the use of a neural network to learn the relationship between vibrational spectra and a multidimensional potential energy surface (PES). The results demonstrate that the neural network is capable of mapping the vibrational motion determined from spectra onto a fully coupled PES with relatively high levels of accuracy.",

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AB - A method for obtaining potential energy surfaces for macromolecules is described. The basis of the method is the use of a neural network to learn the relationship between vibrational spectra and a multidimensional potential energy surface (PES). The results demonstrate that the neural network is capable of mapping the vibrational motion determined from spectra onto a fully coupled PES with relatively high levels of accuracy.

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Potential energy surfaces for macromolecules. A neural network technique

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