No abstract

The Stein Collection in the British Library contains the Diamond Sutra, the world's oldest, dated, printed document. The paper of the Diamond Sutra and other documents from the Stein collection is believed to be dyed yellow by a natural extract, called huangbo, from the bark of Phellodendron amurense, which contains three major yellow chromophores: berberine, palmatine, and jatrorrhizine. Conservation of these documents requires definite information on the chemical composition of the dyes but no suitable, completely noninvasive analytical method is known. Here we report resonance Raman studies of a series of pure dyes, of plant materials and extracts, and of dyed ancient and modern paper samples. Resonance Raman spectroscopy is used to enhance the spectra of the dyes over the signals from the paper matrixes in which they are held. The samples all give resonance Raman spectra which are dominated by intense fluorescence, but by using SSRS (subtracted shifted Raman spectroscopy) we have obtained reliable spectra of the pure dyes, native bark from the Phellodendron amurense, modern paper dyed with huangbo extracted from this bark, and ancient paper samples. For both ancient paper samples whose pigment bands were detected, the relative intensities of the bands due to berberine and palmatine suggest that the ancient paper is richer in berberine than its modern counterpart. This is the first nondestructive in situ method for detection of these pigments in manuscripts, and as such has considerable potential benefit for the treatment of irreplaceable documents that are believed to be dyed with huangbo but documents on which conservation work cannot proceed without definite identification of the chemical compounds that they contain.

No abstract

Background and methodsWall paintings and architectural surfaces in outdoor environments are exposed to several physical, chemical and biological agents, hence they are often treated with different products to prevent or slow down their deterioration. Among the factors that have to be taken into account in the selection of the most suitable treatment for decorated surfaces, the aesthetic compatibility with the substrate is of great importance in the cultural heritage field; minimizing colour variation after treatment application is a crucial issue in particular for painted surfaces. In the framework of the European Project Nanomatch the color variation induced on wall painting mock-ups by the two innovative consolidants (calcium alkoxides) developed was evaluated using colorimetry in comparison with two traditional products. In this work these innovative consolidants have been also tested in combination with two commercial biocides and the results of colorimetric measurements discussed. Moreover, as the univariate approach didn’t allow to draw clear conclusions on the relation between the different sources of data variability, multivariate analysis was performed on colorimetric data.ResultsPrincipal Component Analysis and multi-way Parallel Factor Analysis (PARAFAC) were successfully applied to colorimetric data to investigate the short-term effects of the application of different consolidants on wall painting surfaces, making it possible to study at the same time the different sources of data variability, i.e. treatments, painting techniques, pigments. Finally, a ranking list of the treatments under study in terms of colour variation induced on the surface was established, in function of the painting technique and pigment, taking also in consideration the combination consolidant/biocide. In particular, given the true multi-way nature of the data, PARAFAC model turned out to be extremely useful in the study of the dependence of colour variation on pigments, a critical issue for painted surfaces, that was not clear using univariate approach.ConclusionsMultivariate approach to colorimetric data and especially 3-way PARAFAC method resulted a powerful technique to evaluate in short-term the color compatibility of consolidants for wall paintings, improving data interpretation and visualization, and thus outperforming the univariate statistical analysis.

No abstract