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Slicing - a new method for non destructive 3D elemental sensitive characterization of materials
(2014)
Recent advances in synchrotron sources and detector technology have led to substantial improvements in spatial resolution and detection limits for X-ray fluorescence analysis (XRF). However, the non-destructive three-dimensional elemental sensitive characterization of samples remains a challenge. We demonstrate the use of the so-called 'Color X-ray Camera' (CXC) for 3D measurements for the first time. The excitation of the sample is realized with a thin sheet-beam. The stepwise movement of the sample allows getting the elemental distribution for each layer with one measurement. These layers can be combined to a full 3D dataset for each element afterwards. Since the information is collected layer by layer, there is no need to apply reconstruction techniques, which quite often are the reason for artifacts in the results achieved by computed tomography (CT). The field of applications is wide, as the 3D elemental distribution of a material contains clues to processes inside the samples from a variety of origins. The technique is of special interest and well suited for biological specimens, because their light matrix minimizes restricting absorption effects. Measurement examples of a hornet and the teeth of a Sorex araneus are shown.
Fingerprinting ancient gold work requires the use of nondestructive techniques with high spatial resolution (down to 25 µm) and good detection limits (micrograms per gram level). In this work experimental setups and protocols for synchrotron radiation induced X-ray fluorescence (SRXRF) at the BAMline of the Berlin electron storage ring company for synchrotron radiation (BESSY) in Berlin for the measurement of characteristic trace elements of gold are compared considering the difficulties, shown in previous works, connected to the quantification of Pt. The best experimental conditions and calculation methods were achieved by using an excitation energy of 11.58 keV, a silicon drift chamber detector (SDD) detector, and pure element reference standards. A detection limit of 3 µg/g has been reached. This newly developed method was successfully applied to provenancing the Xiongnu gold from the Gol Mod necropolis, excavated under the aegis of the United Nations Educational, Scientific and Cultural Organization (UNESCO). The composition of the base alloys and the presence of Pt and Sn showed that, contrary to what is expected, the gold foils from the first powerful empire of the steppes along the Great Wall were produced with alluvial gold from local placer deposits located in Zaamar, Boroo, and in the Selenga River.
Partial least squares (PLS) regression-based methods have been proven to be a good alternative for quantification in X-ray fluorescence spectroscopy. These methods are fast and easy to use though giving satisfactory results under certain conditions. One of these conditions is the necessity of having a great number of spectra to build the model (training set). The choice of the constituent concentration range in the training set has a big influence on the accuracy of the model. Better accuracy is obtained if the model is built in relatively narrow regions containing (or close to) the real concentration value.
In the present work, Monte Carlo (MC) simulated spectra are used to form the training set. The advantage to use MC generated training spectra is the unlimited availability of perfect standards.
This paper aims to improve the accuracy of the method by introducing a multiple step procedure in order to build the PLS model using narrow concentration range close to (or containing) the real concentration values in the samples to be measured.
This approach consists of an initial guess of the constituents' concentrations and a preliminary PLS model before building the final model. The prediction of ten MC simulated alloy standard samples containing Ti, Mn, Fe, Co, Cu, Zn, Sr, Zr, and Mo using this method allowed to have average relative prediction errors less than 5% for elements with narrow concentration ranges.