Testing the accuracy of the calculation of gold leaf thickness by mc simulations and MA-XRF scanning

The use of X-ray fluorescence (XRF) scanning systems has become a common practice
in many application sectors. In multistratified and heterogeneous samples, the simple analysis of
an XRF spectrum as a response of the entire sample is not reliable, so di erent spectral analysis
techniques have been proposed to detect the presence of surface stratification. One commonly
studied case is that of gilding, i.e., the presence of a superimposing gold-leaf layer. The observation
of changes in the net peak ratios of a single element or of several elements in an XRF spectrum is
a well-developed practice, but is still not used in the case of XRF scanning (macro-X-Ray fluorescence
scanning, MA-XRF), a technique that can be described as the extrapolation of XRF spot analysis to
a second dimension, scanning a sample surface instead. This practice can yield information on the
overlaying layer thickness, if some properties of the sample are known—or estimated—beforehand,
e.g., the overlapping layer’s chemical composition and the matrix e ect contribution from the bulk
material (thick ratio). This work proposes the use of an algorithm to calculate the thickness distribution
of a superimposing gold layer accurately and automatically through the di erential attenuation
method by using MA-XRF datasets in a total noninvasive manner. This approach has the clear
advantage over the traditional spot sampling of allowing the generation of a surface heightmap to
better visualize and interpret the data, as well as a considerably larger sample space. Monte Carlo
simulations were used to verify the influence of the medium used to adhere the gold leaves to the
substrate and to generate known spectra to assess the algorithm’s accuracy.