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2017 | 132 | 3 | 439-441
Article title

Quantitative Characteristic X-Ray Analysis for Different Compound Samples by Using Monte Carlo Method

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EN
Abstracts
EN
X-ray spectrometry is an elemental analysis technique with broad application in science and industry. It is based on the principle that individual atoms, when excited by an external energy source emit X-ray photons of a characteristic energy or wavelength. Here we obtained the characteristic X-ray peaks of different brass compounds and compared the intensity of characteristic peaks by changing with Zn rate. In this study we modelled different brass samples by using Monte Carlo method and changed the zinc rate in brass samples for each compound. We obtained the characteristic X-ray peaks of different compounds and compared the intensity of characteristic peaks by changing with Zn rate. We achieved a good agreement between peak intensity and corresponding element rate in compound. Also we obtained that characteristic peak rate increases by corresponding element rate in compound. This study shows that Monte Carlo method is very effective method to simulate material features due to their characteristic peaks and their intensities.
Keywords
Publisher

Year
Volume
132
Issue
3
Pages
439-441
Physical description
Dates
published
2017-09
Contributors
author
  • Uskudar University, Vocational School of Health Service, Radiotherapy Department, Istanbul, Turkey
  • Uskudar University, Vocational School of Health Service, Medical Imaging Department, Istanbul, Turkey
  • Uskudar University, Medical Radiation Research Center (USMERA), Istanbul, Turkey
author
  • Uskudar University, Vocational School of Health Service, Medical Imaging Department, Istanbul, Turkey
  • Uskudar University, Medical Radiation Research Center (USMERA), Istanbul, Turkey
author
  • Uskudar University, Medical Radiation Research Center (USMERA), Istanbul, Turkey
author
  • Okan University, Faculity of Medicine, Department of Radiology, Istanbul, Turkey
References
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-appv132n3p008kz
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