Description

The collection of the Museum Plantin-Moretus consists of a large variety of historical typographical items. Amongst them are sets of copper matrices, which are the ‘dies’ for casting lead printing letters (‘type’). They are of foremost interest for the research of typography and have been studied thoroughly in the past decades, mainly through visual comparison and extensive research in the Plantin archives and books which were printed with type cast from the matrices. Until now, there has never been an attempt to apply analytical measuring techniques. The main reason for this is the vast number of matrices (about 20,000 pieces) and the fact that they may not leave the museum nor may they be damaged for destructive analysis. Also, the majority of matrices are made of copper and were never investigated towards possible material variations to differentiate them from each other.

In this article, X-Ray Fluorescence (XRF) is investigated to provide analytical results on the copper compositions. As a first step, the analytical method is evaluated on a relatively small number of matrices (i.e. nearly 1,000 items) to determine to what level the results may serve as information. Five sets of matrices, which were supplied by Granjon to Plantin in 1574, were measured to act as a benchmark for the applied analytical technique. A related set of matrices and two other sets as case studies were also analysed. The elements present in the matrices, besides the copper, were measured and quantified to distinguish individual matrices within a set and to distinguish sets of matrices from each other.

Starting from the metal composition of the matrices, multivariate methods including cluster analysis and principal component analysis, were applied to reveal the hidden structure in the elemental data. The compositional similarities or differences were mapped and linked to historical information, allowing to correlate the chemical composition with the makers, time or location of the matrices. These analyses may lead to future insights about the attributions of the sets of matrices and perhaps reveal correlations beyond archival evidence or visual comparison.