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Removal of small parasite peaks in powder diffraction data by a multiple deconvolution method

Published online by Cambridge University Press:  29 June 2018

Takashi Ida*
Affiliation:
Advanced Ceramics Research Center, Nagoya Institute of Technology, Asahigaoka, Tajimi, Gifu 507-0071, Japan
Shoki Ono
Affiliation:
Advanced Ceramics Research Center, Nagoya Institute of Technology, Asahigaoka, Tajimi, Gifu 507-0071, Japan
Daiki Hattan
Affiliation:
Advanced Ceramics Research Center, Nagoya Institute of Technology, Asahigaoka, Tajimi, Gifu 507-0071, Japan
Takehiro Yoshida
Affiliation:
Advanced Ceramics Research Center, Nagoya Institute of Technology, Asahigaoka, Tajimi, Gifu 507-0071, Japan
Yoshinobu Takatsu
Affiliation:
Advanced Ceramics Research Center, Nagoya Institute of Technology, Asahigaoka, Tajimi, Gifu 507-0071, Japan
Katsuhiro Nomura
Affiliation:
Inorganic Functional Materials Research Institute, National Institute of Advanced Industrial Science and Technology, Anagahora, Shimoshidami, Moriyama, Nagoya, Aichi 463-8560, Japan
*
a)Author to whom correspondence should be addressed. Electronic mail: ida.takashi@nitech.ac.jp

Abstract

Four series of small parasite peaks observed in powder diffraction data recorded with a Cu-target X-ray tube and a Ni filter on the diffracted beam side in Bragg–Brentano geometry are investigated. One series of the parasite peaks is assigned to the tungsten -emission. Other three types of the parasite peak series are likely to be caused by the K-emissions of Ni, but the peak locations are deviated from those predicted by the Bragg's law. An empirical formula to locate the parasite peaks and a method to remove them from observed powder diffraction data are proposed. The method is based on the whole-pattern deconvolution–convolution treatment on the transformed scale of abscissa. The parameters optimized for the diffraction data measured for Si powder has been applied on treatment of the data of LaB6 powder recorded under the same experimental conditions. It has been confirmed that the parasite peaks in the observed data can effectively be removed by the deconvolution treatment with parameters determined by a reference measurement.

Type
Technical Article
Copyright
Copyright © International Centre for Diffraction Data 2018 

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References

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