X-ray Fluorescence (XRF) Spectroscopy
​X-ray Fluorescence is a technique that can provide information on which chemical elements are present in a material. It is often used alongside other techniques such as Raman Spectroscopy or Spectral Imaging to provide complementary information and a more comprehensive identification of the materials present.
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The ISAAC XRF systems can be used for point-based analysis, or by scanning and collecting XRF spectra over a region, an XRF spectral cube can be constructed which allows the elemental mapping of an area of interest.​
Portable XRF spectrometer being used to analyse the Canterbury Roll
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applications of xrf spectroscopy
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Assistance in identification of inorganic pigments and the presence of ground layers
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Examination of the elemental composition of glass​​
The Bruker Crono XRF System analysing a large format Chinese painting at the National Museum of Asian Art, Smithsonian Institution
isaac instrumentation
System
Portable XRF​
(Niton XL3t Analyser)
XRF Scanner (CRONO)​​​​
Developer
Thermo-Fischer Scientific
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Bruker
Spot Size*
3 mm / 8 mm
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0.5 mm/ 1 mm/
2 mm
Max Scanning Area
N/A
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1 m x 1 m
Spectral
Range
1 keV- 50 keV
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1 keV- 50 keV
Working
Distance
~ 1 mm
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5-7 mm
Service
MOLAB/
FIXLAB
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MOLAB/
FIXLAB​​
* Spot size is dependent on instrument configuration
example heritage science projects
selected publications
This is a selection of our XRF publications. Our full publication list can be found here.
Botteon, A., Conti, C., Colombo, C., Catrambone, M., Realini, M., Miliani, C., Kogou, S., Cheung, S., Liang, H., Tasso, F., Palazzo, M. & Sansonetti, A. 2025. Multimodal and multiscale non-invasive study of Leonardo’s mural painting in Sala delle Asse (Milan): A tool supporting cleaning evaluation. Journal of Cultural Heritage 75, 217-225. https://doi.org/10.1016/j.culher.2025.07.017
Liang, H., Butler, L., Kogou, S., Burke, M., Lee, L., Pereira Pardo, L., Angelova, L., France, F. & McCarthy, B. (2024). From Lima to Canton and Beyond: Mobile and Digital Research Infrastructure for Closing the Gap Between Resource-rich and Resource-poor Organisations. Studies in Conservation, 69(sup1), 198–207. Contributions to the Lima Congress 2024.Sustainable Solutions for Conservation: New Strategies for New Times. https://doi.org/10.1080/00393630.2024.2336801
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Kogou, S., Shahtahmassebi, G., Lucian, A., Liang. H, Shui, B., Zhang, W., Su, B. and van Schaik, S. 2020. From remote sensing and machine learning to the history of the Silk Road: large scale material identification on wall paintings. Sci Rep 10, 19312 (2020). https://doi.org/10.1038/s41598-020-76457-9
Kogou, S., Lee, L., Shahtahmassebi, G. and Liang, H., 2020. A New Approach to the Interpretation of XRF Spectral Imaging Data Using Neural Networks. X-Ray Spectrometry https://doi.org/10.1002/Xrs.3188
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