Estimation of cross sections for molecule-cluster interactions by using artificial neural networks

BÖYÜKATA M., Kocyigit Y., Guvenc Z. B.

BRAZILIAN JOURNAL OF PHYSICS, vol.36, no.3A, pp.730-735, 2006 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 3A
  • Publication Date: 2006
  • Journal Name: BRAZILIAN JOURNAL OF PHYSICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.730-735
  • Keywords: artificial neural networks, molecular dynamics, clusters, reactivity, DISSOCIATION DYNAMICS, NI CLUSTERS, NI(111) SURFACES, NICKEL CLUSTERS, METAL-CLUSTERS, HYDROGEN, SYSTEMS, H-2, D2, REACTIVITY
  • Yozgat Bozok University Affiliated: Yes

Abstract

The cross sections Of D(2) (v,j) + Ni(n) (T), n = 19 and 20, collision systems have been estimated by using Artificial Neural Networks (ANNs). For training, previously determined cross section values via molecular dynamics simulation have been used. The performance of the ANNs for predicting any quantities in molecule-cluster interaction has been investigated. Effects of the temperature of the clusters and the rovibrational states of the molecule are analyzed. The results are in good agreement with previous studies.