Scanning macro-X-ray fluorescence analysis (MA-XRF) is rapidly being established as a technique for the investigation of historical paintings. The elemental distribution images acquired by this method allow for the visualization of hidden paint layers and thus provide insight into the artist's creative process and the painting's conservation history. Due to the lack of a dedicated, commercially available instrument the application of the technique was limited to a few groups that constructed their own instruments. We present the first commercially available XRF scanner for paintings, consisting of an X-ray tube mounted with a Silicon-Drift (SD) detector on a motorized stage to be moved in front of a painting. The scanner is capable of imaging the distribution of the main constituents of surface and sub-surface paint layers in an area of 80 by 60 square centimeters with dwell times below 10 ms and a lateral resolution below 100 μm. The scanner features for a broad range of elements between Ti (Z = 22) and Mo (Z = 42) a count rate of more than 1000 counts per second (cps)/mass percent and detection limits of 100 ppm for measurements of 1 s duration. Next to a presentation of spectrometric figures of merit, the value of the technique is illustrated through a case study of a painting by Rembrandt's student Govert Flinck (1615–1660).

Elemental distribution maps are of great interest in the study of historical paintings, as they allow to investigate the pigment use of the artist, to image changes made in the painting during or after its creation and in some cases to reveal discarded paintings that were later over painted. Yet a method that allows to record such maps of a broad range of elements in a fast, non-destructive and in situ manner is not yet commonly available; a dedicated mobile scanning XRF instrument might fill this gap. In this paper we present three self-built scanning macro-XRF instruments, each based on the experience gained with its precursor. These instruments are compared in terms of sensitivity and limits of detection, which includes a discussion of the use of polycapillary optics and pinhole collimators as beam defining devices. Furthermore, the imaging capabilities of the instruments are demonstrated in three exemplary cases: (parts of) historical paintings from the 15^th to the 19^th century are examined. These cases illustrate the value of element specific distribution maps in the study of historical paintings and allow in the case of Vincent van Gogh's “Patch of Grass” a direct comparison between in situ and synchrotron based scanning macro-XRF.

Technical progress in the fields of X-ray sources, optics and detectors is constantly enhancing the pace of data acquisition in XRF imaging. This enlarges the size of the hyperspectral datasets and the number of their sub-parts. This paper describes the challenges in processing large XRF datasets featuring several million pixels/spectra and the strategies developed to overcome them. During the investigation of historical paintings by scanning macro-XRF the main challenges are the correct identification of all spectral features in a dataset and its timely processing. For the identification of spectral features different approaches are discussed, i.e. the use of sum spectra, maximum pixel spectra and of χ_r ² maps. For the time-efficient, artefact-free evaluation of XRF imaging data, different software packages are evaluated and intercompared (AXIL, PyMCA, GeoPIXE and the in-house written datamuncher). The process of data evaluation is illustrated on a large dataset (3.4 MPixels) acquired during the investigation of a version of Caravaggio's Supper at Emmaus (143 × 199.5 cm²). This 17th century painting is currently the largest object entirely scanned with macroscopic XRF.