Prediction of First Order Focusing Properties of Ideal Hemispherical Deflector Analyzer Using Artificial Neural Network

• Authors: N. Isik , A. Isik , O. Sise , U. Guvenc
• Languages of publication: EN

Abstracts

EN

Electrostatic energy analyzers are irreplaceable instruments to analyze the electron beams energies. In this context, the knowledge of electron trajectories in electrostatic energy analyzers has major importance in collision physics as well as in different scientific instruments for surface science. In this study, electron trajectories for different energies in an ideal field 180° hemispherical deflector analyzer are investigated by artificial neural network prediction method. The SIMION 8.1 simulation program is used as a data source for training and testing of artificial neural network. Artificial neural network based prediction has been performed using Matlab R2012b program. Obtained performance results indicate that this approach provides new perspectives for the rapid solution to the problems in charged particle optics.

Keywords

EN

42.79.Fm; 07.05.Tp

Discipline

• 42.79.Fm: Reflectors, beam splitters, and deflectors
• 07.05.Tp: Computer modeling and simulation

• Publisher: Institute of Physics, Polish Academy of Sciences
• Journal: Acta Physica Polonica A
• Year: 2017
• Volume: 131
• Issue: 1
• Pages: 10-12

Dates

published

2017-01

Contributors

author

N. Isik

• Mehmet Akif Ersoy University, Department of Science Education, 15030 Burdur, Turkey

author

A. Isik

• Mehmet Akif Ersoy University, Department of Computer Engineering, 15030 Burdur, Turkey

author

O. Sise

• Süleyman Demirel University, Department of Science Education, 32260 Isparta, Turkey

author

U. Guvenc

• Duzce University, Department of Electrical and Electronics Engineering, 81620 Duzce, Turkey

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Identifiers

DOI

10.12693/APhysPolA.131.10