Prediction of First Order Focusing Properties of Ideal Hemispherical Deflector Analyzer Using Artificial Neural Network
Yükleniyor...
Dosyalar
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Polish Acad Sciences Inst Physics
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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 degrees 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.
Açıklama
6th Congress and Exhibition on International Advances in Applied Physics and Materials Science (APMAS) -- JUN 01-03, 2016 -- Istanbul, TURKEY
GUVENC, Ugur/0000-0002-5193-7990
WOS: 000396118600003
GUVENC, Ugur/0000-0002-5193-7990
WOS: 000396118600003
Anahtar Kelimeler
Kaynak
Acta Physica Polonica A
WoS Q Değeri
Q3
Scopus Q Değeri
Q4
Cilt
131
Sayı
1
