Michal Čeppan

Chemometric tool for identification of iron–gall inks by use of visible–near infrared fibre optic reflection spectroscopy

AbstractA method has been developed for identification of corrosive iron–gall inks in historical drawings and documents. The method is based on target-factor analysis of visible–near infrared fibre optic reflection spectra (VIS–NIR FORS). A set of reference spectra was obtained from model samples of laboratory-prepared inks covering a wide range of mixing ratios of basic ink components deposited on substrates and artificially aged. As criteria for correspondence of a studied spectrum with a reference spectrum, the apparent error in target (AET) and the empirical function SPOIL according to Malinowski were used. The capability of the proposed tool to distinguish corrosive iron–gall inks from bistre and sepia inks was evaluated by use of a set of control samples of bistre, sepia, and iron–gall inks. Examples are presented of analysis of historical drawings from the 15th and 16th centuries and written documents from the 19th century. The results of analysis based on the tool were confirmed by XRF analysis and colorimetric spot analysis. FigureSitting Evangelist, Bartolomeo Passarotti, 16th century, Slovak National Gallery, Bratislava, Slovak Republic, Inventory No. K 96

Principal component analysis for the forensic discrimination of black inkjet inks based on the Vis–NIR fibre optics reflection spectra

Nineteen black inkjet inks of six different brands were examined by fibre optics reflection spectroscopy in Visible and Near Infrared Region (Vis-NIR FORS) directly on paper with a view to achieving good resolution between them. These different inks were tested on nineteen different inkjet printers from three brands. Samples were obtained from prints by reflection probe. Processed reflection spectra in the range 500-1000 nm were used as samples in principal component analysis. Variability between spectra of the same ink obtained from different prints, as well as between spectra of square areas and lines was examined. For both spectra obtained from square areas and lines reference, Principal Component Analysis (PCA) models were created. According to these models, the inkjet inks were divided into clusters. PCA method is able to separate inks containing carbon black as main colorant from the other inks using other colorants. Some spectra were recorded from another piece of printer and used as validation samples. Spectra of validation samples were projected onto reference PCA models. According to position of validation samples in score plots it can be concluded that PCA based on Vis-NIR FORS can reliably differentiate inkjet inks which are included in the reference database. The presented method appears to be a suitable tool for forensic examination of questioned documents containing inkjet inks. Inkjet inks spectra were obtained without extraction or cutting sample with possibility to measure out of the laboratory.

Differentiation of selected blue writing inks by surface-enhanced Raman spectroscopy

Raman spectroscopy and surface enhanced Raman spectroscopy were used to examine 14 blue inks obtained from commercially available stationery. Standard colouring agents in the inks: β-phase of phtalocyanine blue PB15 and some homologues of the methyl violet class, were identified. Surface enhanced Raman spectra were recorded on a firm heterostructure of silver/nanocrystalline diamond/silicon constituting an active substrate providing the possibility to write directly on the surface. Based on the differences in traditional and surface enhanced Raman spectra, two inks were identified unambiguously, the remaining inks were categorised into three groups exhibiting common spectral features. Despite their similarity, surface enhanced Raman spectra exhibited soft variations enabling discrimination of the inks, thus proving the usefulness of the method.

Pre-processing of inkjet prints NIR spectral data for principal component analysis

Abstract This paper presents a novel approach in non-destructive analysis of inkjet-printed documents. Our method is based on the combination of molecular spectroscopy in the Near Infrared Region (NIR) and a chemometric method - principal component analysis (PCA). The aim of this work was to prepare spectral data for the analysis of the interrelationships between 19 samples consisting of the same type of office paper on which black squares were full printed in black ink only. The spectra were obtained separately using the Ocean Optics System in two spectral regions, i.e., overtones: 1000-1600 nm and combination bands: 1600-2300 nm, with the paper base. Experimental results confirmed the high reliability of the proposed approach despite the sparse dataset.

Study of Vis-NIR and NIR spectral data of black inkjet prints using principal component analysis for forensic discrimination:

The aim of this work was to prepare spectral data for principal component analysis and to examine 19 samples of six different brands. Samples consisted of the same type of office paper with black areas printed in black ink only. The spectral data were acquired by fibre optics reflection spectroscopy in Vis-NIR and only NIR (Vis-NIR FORS) directly on paper. The black inkjet-printed samples were analysed with regard to the forensic analysis of documents. The method used is based on the combination of molecular spectroscopy in the visible (Vis) and near infrared region (NIR) combined with a chemometric method, – principal component analysis (PCA). The PCA method divides the inkjet inks sample into clusters. It was found out that by a combination of spectrum pre-processing methods and principal component analysis, it is possible to separate inks containing carbon black from the other inks using other organic colourants. This method appears to be a useful tool for forensic examination of printed documents containing inkjet inks. Spectra of inkjet inks were acquired without any destructive or invasive procedure, for example cutting sample or for extraction with the possibility to measure out of the laboratory.