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International Journal of Architectural Heritage
Conservation, Analysis, and Restoration
Volume 18, 2024 - Issue 1
176
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Research Article

p-XRF for the Detection of the Elemental Content in the Glaze Layer of Chinese Glazed Tiles

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Pages 150-163 | Received 26 Feb 2022, Accepted 21 Sep 2022, Published online: 05 Oct 2022
 

ABSTRACT

This study was performed to eliminate large errors during the portable X-ray fluorescence (p-XRF) analysis of elements present in the glaze layer of glazed tiles and to establish a new calibration method, namely body-glaze fitting, by using a binary linear regression model for five typical elements of Pb, Cu, Al, Si, and Mg available in the glaze layer by employing reference experimental samples. The method was used to calibrate the results of 10 glazed tile samples from four different origins and compare these calibration results with the findings of the conventional reference material method. Scientific assay validity and calibration result reliability were assessed using the laboratory methods of energy-dispersive spectroscopy mapping and energy-dispersive X-ray fluorescence. Finally, the novel calibration method was confirmed to be suitable for the traceability of the glazed tiles on the basis of elemental concentrations. The results showed that the quality of body-glaze fitting calibration data was satisfactory and met p-XRF requirements for the quantitative analysis of the glazed tiles. Moreover, the calibrated data revealed the craftsmanship provenance of the glazed tiles to improve the research on the history of ancient Chinese architecture and help the restoration and protection of Chinese architectural heritage glazed tile materials.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant 51778402 and the National Key Research and Development Program of China under Grant 2020YFC1522400.

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