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Bayesian inference massively cuts XRF analysis time

24 January 2023 | News
by Ian Michael
X-ray fluorescence spectra at 1, 3, 5 and 3600 seconds.

X-ray fluorescence (XRF) analysis can be used to identify an abundance of elements, e.g. to detect toxic heavy metals levels in soil. Current methods of XRF analysis take about 10 minutes to accurately identify elements, so new methods that can measure large quantities or take multiple measurements of unknown materials quickly are desired.

A joint research group, including Dr Tsugufumi Matsuyama, Professor Kouichi Tsuji and Masanori Nakae, a second-year master's student at the Osaka Metropolitan University Graduate School of Engineering, and researchers from the Japan Atomic Energy Agency, has developed a new method by applying Bayesian estimation to XRF analysis. The group succeeded in reducing the measurement time of an XRF spectrum per measurement point, from 7 s to 3 s—reducing the time needed by 4 s to obtain analysis results that were not significantly different to the spectra obtained from measuring a glass standard sample for one hour. For example, when creating an elemental distribution, as many as 10,000 measurements may be taken, over a small area, depending on the sample. So, reducing the measurement time per point by 4 s can reduce the total measurement time by 40,000 seconds—about 11 hours—when creating an elemental distribution.

Dr Matsuyama stated, “We have successfully integrated analytical chemistry and informatics, using applied Bayesian inference to XRF analysis. Further studies are needed to determine whether it is possible to use this method to detect trace amounts of elements. If we can perform rapid elemental analysis in a non-destructive manner without needing to contact the sample, this technique could be popular in many fields, such as analysis of industrial products or waste materials carried on conveyor belts, and monitoring of ongoing chemical reactions.”


Read the original journal paper in Spectrochimica Acta B

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