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Attenuated total reflection‐Fourier transform‐infrared spectroscopy (ATR‐FT‐IR) analysis of 100 adhesive samples from different prehistoric composite artefacts, pottery, and amorphous lumps across Eastern Europe and Urals were conducted with the aim to establish a fast analytical screening method for adhesive assignment. The ATR‐FT‐IR analysis allowed the identification of major chemical components of the adhesive samples that were assigned to three main groups: birch bark tar without major additives, birch bark tar with additives, and minor/non‐birch bark tar samples. ATR‐FT‐IR spectra were further analyzed using principal component analysis (PCA)‐based discriminant analysis (DA) that allowed additional refinement of adhesive classifications. The ATR‐FT‐IR results and the DA classification were confirmed by analyzing a selection of samples with gas chromatography–mass spectrometry (GC–MS). Results demonstrate that ATR‐FT‐IR coupled with DA classification allows fast and reliable preliminary identification of the major components in archaeological adhesives and their further classification. As such it is a considerable and faster alternative to more laborious GC–MS analysis, especially in the case of very small samples. [ABSTRACT FROM AUTHOR]

The possibility of classification of single- and two-component textile materials using ATR-FT-IR spectra and chemometric methods, principal component analysis (PCA) and discriminant analysis, was assessed. Altogether 89 textile samples belonging to 26 different types (11 one- and 15 two-component textiles) were investigated. It was found that PCA classification using only two or three principal components (PCs) enables identifying different one- and two-component textiles, although with two important limitations: it was not always possible to distinguish between the cellulose-based fibres (cotton, linen and in some cases viscose) and it was only partly possible to distinguish between silk and wool. The statistical discriminant analysis can use as many PCs as there are sample classes and due to that can discriminate between single-component fibres, including viscose from linen and cotton as well as silk from wool. Besides that, in both of these cases, involving optical microscopy as an additional technique enabled unequivocal identification of the fibres. The possibilities of semi-quantitative analysis of mixed fibres (cotton-polyester, wool-polyester and wool-polyamide) with PCA were investigated and it was found that approximate quantitative composition is obtainable if for the mixed fibre sample a number of spectra are averaged in order to minimize the effect of structural inhomogeneity. For approximate content determination 25 spectra of selected two-component samples were registered for calibration and the averaged spectrum for each sample was computed. Due to the structural inhomogeneity of mixed textiles, obtaining accurate quantitative composition from real samples is not possible with ATR-FT-IR. The main problems with ATR-FT-IR-PCA classification are (1) difficulties in getting high quality spectra from some textiles (e.g. polyacrylic), (2) inhomogeneity of the textile fibres in the case of two-component fibres and (3) intrinsic similarity between the spectra of some fibres (e.g. cotton and linen). In order to test the homogeneity of mixed fibres, microscopic and IR-microspectroscopic analysis was carried out. [ABSTRACT FROM AUTHOR]