Abstract: The speed and effectiveness of a conservation treatment used for stained glass windows have been investigated. Dark-coloured Mn-rich stains can be found in the alteration layer of ancient glass artefacts and cause the surface to turn brown/black: this phenomenon is known as Mn-browning or Mn-staining. While in glass manganese is present in the +II or +III oxidation states, in the Mn-rich bodies, manganese is in a higher oxidation state (+IV). In restoration practice, mildly reducing solutions are employed to eliminate the dark colour and restore the clear appearance of the glass. In this paper the effectiveness and side effects of the use of hydroxylamine hydrochloride for this purpose are assessed. Archaeological fragments of stained glass windows, dated to the 14th century and originating from Sidney Sussex College, Cambridge (UK), were examined by means of synchrotron radiation (SR) based microscopic X-ray Absorption Near-Edge Spectroscopy (μ-XANES) and microscopic X-Ray Fluorescence (μ-XRF) and with high resolution computed absorption tomography (μ-CT) before, during and after the treatment. The monitoring of the glass fragments during the treatment allows us to better understand the manner in which the process unfolds and its kinetics. The results obtained reveal that the hydroxylamine hydrochloride treatment is effective, but also that it has a number of unwanted side effects. These findings are useful for optimizing the time and other modalities of the Mn-reducing treatment as well as minimizing its unwanted results.

Abstract: X-ray radiographic images of paintings often show little or no contrast. In order to increase the contrast in radiographic images we measured the X-ray spectrum of a low power X-ray tube, after passing through the painting, with a high energy-resolution SDD detector. To obtain images, the detector is collimated with a 400 mu m diameter pinhole and the painting was moved through the beam in the x and y-direction using a dwell time of a few seconds per pixel. The data obtained consists of a data cube of, typically, 200 x 200 pixels and a 512-channel X-ray spectrum for each pixel, spanning the energy range from 0 to 40 keV. Having the absorbance spectrum available for each pixel, we are able, a posteriori, to produce images by edge subtraction for any given element. In this way high contrast, element-specific, images can be obtained. Because of the high energy-resolution a much simpler edge subtraction algorithm can be applied. We also used principal-component imaging to obtain, in a more automated way, images with high contrast. Some of these images can easily be attributed to specific elements. It turns out that preprocessing of the spectral data is crucial for the success of the multivariate image processing.