Spectrum adapted expectation-conditional maximization algorithm for extending high-throughput peak separation method in XPS analysis

被引:8
|
作者
Matsumura, Tarojiro [1 ]
Nagamura, Naoka [2 ,3 ]
Akaho, Shotaro [4 ]
Nagata, Kenji [2 ,3 ]
Ando, Yasunobu [1 ]
机构
[1] Natl Inst Adv Ind Sci & Technol, Res Ctr Computat Design Adv Funct Mat CD FMat, Tsukuba, Ibaraki 3058568, Japan
[2] Natl Inst Mat Sci NIMS, Res Ctr Adv Measurement & Characterizat, Tsukuba, Japan
[3] Japan Sci & Technol Agcy, PRESTO, Kawaguchi, Japan
[4] Natl Inst Adv Ind Sci & Technol, Artificial Intelligence Res Ctr AIRC, Tokyo, Japan
关键词
Peak fitting; X-ray photoelectron spectroscopy; expectation-conditional maximization algorithm; high-throughput analysis; X-RAY PHOTOEMISSION; LINE; DECONVOLUTION; LAYERS; VOIGT;
D O I
10.1080/27660400.2021.1899449
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
We introduced the spectrum-adapted expectation-conditional maximization (ECM) algorithm to improve the efficiency of the peak fitting of spectral data by various fitting models. The spectrum-adapted ECM algorithm can perform the peak fitting by using the Pseudo-Voigt mixture model and Doniach-& Scaron;unji & cacute;-Gauss mixture model which are generally used for the peak fitting in the X-ray photoelectron spectroscopy. Analyses of the synthetic and experimental spectral data showed that the proposed method quickly completed the calculation and estimated well-fitted curves to spectral data. This result suggests that the spectrum adapted ECM algorithm efficiently perform the peak fitting for large number of spectral data sets.
引用
收藏
页码:45 / 55
页数:11
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