The Monte Carlo—Library Least-Squares approach for energy-dispersive x-ray fluorescence analysis
作者： T. He , R.P. Gardner , K. Verghese
DOI: 10.1016/0969-8043(93)90089-S
关键词: Trace (linear algebra) 、 Monte Carlo method 、 Energy (signal processing) 、 Excited state 、 Spectral line 、 Photoelectric effect 、 X-ray fluorescence 、 Mineralogy 、 Computational physics 、 Chemistry 、 Least squares
摘要: Abstract A new analysis principle called Monte Carlo—Library Least-Squares (MCLLS) approach has been identified and investigated for quantitative energy dispersive x-ray fluorescence analyses. The feasibility of the MCLLS with a radioisotope source excited EDXRF analytical system several standard samples known composition. With good initial elemental composition guesses, results showed excellent agreement compositions in samples. Furthermore, by taking ratio photoelectric peak counts sample experimental spectra as approximate proposed iterative algorithm works quite well, converging to correct compositions. Only one iteration was needed all major elements. For trace elements second some cases. Other possible applications future work are also discussed.
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