Estimation of Cross Sections for Molecule-Cluster Interactions by Using Artificial Neural Networks
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Date
2006
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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.
Description
Kocyigit, Yucel/0000-0003-1785-198X
ORCID
Keywords
Artificial Neural Networks, Molecular Dynamics, Clusters, Reactivity, Clusters, Reactivity, Molecular Dynamics, Artificial Neural Networks
Fields of Science
0103 physical sciences, 01 natural sciences
Citation
WoS Q
Q3
Scopus Q
Q3

OpenCitations Citation Count
2
Source
4th Brazilian Meeting on Simulational Physics -- AUG 09-12, 2005 -- Ouro Preto, BRAZIL
Volume
36
Issue
3A
Start Page
730
End Page
735
PlumX Metrics
Citations
CrossRef : 1
Scopus : 3
Captures
Mendeley Readers : 2
SCOPUS™ Citations
4
checked on Feb 24, 2026
Web of Science™ Citations
2
checked on Feb 24, 2026
Page Views
1
checked on Feb 24, 2026
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