Paintings are subject to various alterations over time and nowadays often have a different appearance than originally intended by the artist. In this research project, we want to visualize – in 3D – the degradation processes that take place in the painting, specifically the degradation of arsenic- and lead-containing pigments.
A better understanding is necessary in order to delay or completely stop these degradation processes. To achieve this, data fusion technology will be used, a technology that is already used in heterogeneous catalyst research to combine various types of imaging information in 3D. This involves combining 2D distribution maps of the paint components on the macroscopic and microscopic scales, spectroscopic information and 3D density volumes obtained by computer tomography. The generated model provides a 3D image of the paint composition making it possible to visualize the degradation and migration processes in the paint layers in relation to the paint surface.
Such knowledge is relevant to conservators for a better understanding of paint degradation phenomena in order to develop and tailor more appropriate conservation treatments. For art historians, the 3D models of the paint build-up will provide insight and a means to obtain a better understanding of the techniques employed by the artists involved.