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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

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Publicly Funded

No
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Average
Influence
Top 10%
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Average

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Journal Issue

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

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
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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
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Citations

CrossRef : 1

Scopus : 3

Captures

Mendeley Readers : 2

SCOPUS™ Citations

4

checked on Feb 24, 2026

Web of Science™ Citations

2

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Page Views

1

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0.19025375

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