Description of the potential energy surface of the water dimer with an artificial neural network

A potential energy function for the water dimer has been developed with an artificial neural network (back propagation of error algorithm). The potential energy surface was obtained with 6s3p3d/3s3p MP2 ab initio MO calculations. The trained neural network reproduced the potential energy surface of...

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Bibliographic Details
Published inChemical physics letters Vol. 271; no. 1; pp. 152 - 156
Main Authors Tai No, Kyoung, Ha Chang, Byung, Yeon Kim, Su, Shik Jhon, Mu, Scheraga, Harold A.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 06.06.1997
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Summary:A potential energy function for the water dimer has been developed with an artificial neural network (back propagation of error algorithm). The potential energy surface was obtained with 6s3p3d/3s3p MP2 ab initio MO calculations. The trained neural network reproduced the potential energy surface of the water dimer very well, not only in the low-energy region but also in the high-energy region.
ISSN:0009-2614
1873-4448
DOI:10.1016/S0009-2614(97)00448-X