Estimation of semiconductor-like pigment concentrations in paint mixtures and their differentiation from paint layers using first-derivative reflectance spectra.

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Pallipurath, Anuradha R 
Skelton, Jonathan M 
Elliott, Stephen R 

Identification of the techniques employed by artists, e.g. mixing and layering of paints, if used together with information about their colour palette and style, can help to attribute works of art with more confidence. In this study, we show how the pigment composition in binary paint mixtures can be quantified using optical-reflectance spectroscopy, by analysis of the peak features corresponding to colour-transition edges in the first-derivative spectra. This technique is found to be more robust than a number of other spectral-analysis methods, which can suffer due to shifts in the transition edges in mixed paints compared to those observed in spectra of pure ones. Our method also provides a means of distinguishing paint mixtures from layering in some cases. The spectroscopy also shows the presence of multiple electronic transitions, accessible within a narrow energy range, to be a common feature of many coloured pigments, which electronic-structure calculations attribute to shallow band edges. We also demonstrate the successful application of the reflectance-analysis technique to painted areas on a selection of medieval illuminated manuscripts.

Deconvolution, Electronic-structure calculations, Fibre-optic reflectance spectroscopy, First-derivative analysis, Function fitting, Lead-tin yellow, Paint mixtures, Red lead, Vermillion
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Elsevier BV
ARP is indebted to St. John’s College, Cambridge for providing a scholarship to fund this study, and to ASD Inc. (through the Alexander Goetz programme) and Analytik UK Ltd. for the loan of a Fieldspec 4 spectroradiometer for the completion of this work. JMS is indebted to Trinity College, Cambridge for provision of an Internal Graduate Studentship, and to the UK Engineering and Physical Sciences Research Council (EPSRC) for support under grant no. EP/K004956/1. The computational modelling was performed on the UK national HPC facility (Archer), accessed through the Materials Chemistry Consortium, which is funded through EPSRC grant no. EP/L000202.