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

Kyoung Tai No, Byung Ha Chang, Su Yeon Kim, Mu Shik Jhon, Harold A. Scheraga

Research output: Contribution to journalArticle

44 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)152-156
Number of pages5
JournalChemical Physics Letters
Volume271
Issue number1-3
DOIs
Publication statusPublished - 1997 Jun 6

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

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