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Only black inkjet prints were studied with regard to forensic examination of documents. We analysed twenty-one inkjet prints using surface-enhanced infrared absorption spectroscopy (SEIRAS). The present paper deals with micro-destructive document analysis based on silver nanoparticles (AgNPs) use to obtain surface enhanced ATR-FTIR (attenuated total reflection -- Fourier transform infrared) spectra directly from the document. For this experiment, AgNPs in colloid form was applied. AgNPs for SEIRAS analyses were synthesised and afterwards analysed by scanning electron microscopy (SEM). The purpose of the enhancement of colloids was to improve the resolution of the absorption signal of the analysed samples from noise. In the experiment, the obtained ink ATR-FTIR spectra, with and without silver treatment, were significantly affected by the paper base. [ABSTRACT FROM AUTHOR]

This work presents a study regarding the forensic discrimination of black inkjet-printed documents in question. Nondestructive Fourier transform near-infrared (FT-NIR) spectroscopy in combination with supervised classification method Discriminant Analysis (DA); Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) were utilized to investigate 22 different prints of the three most sold office printer brands. The spectra were acquired using the FT-NIR spectrometer NIRFlex N-500 (Büchi Labortechnik AG, Flawil, Switzerland) with the Fiber Optic Solids measuring cell in the spectral region of 10,000-4000 cm-1. Each sample was printed on the same type of office paper. The spectra were 45 times acquired on 3 separate printed squares of each sample. It results in 990 acquired spectra for the presented experiment. The FT-NIR spectra of the printed squares were split into calibration and test sets with which the Classification accuracy (CA) value of unknown samples was evaluated. In order to increase the significance, three different compilations of calibration and test sets were realized. The performance of three different Discriminant model methods; LDA (Euclidean and Mahalanobis algorithm) and QDA were compared to each other. Furthermore, the CA of each DA method was examined using 1-5 principal components (PCs) in the construction of the respective DA model. Two groups of models, according to the ink subset (Carbon black and Black colorant), were performed in raw and Standard Normal Variate (SNV) correction spectra alternations. The results showed that the Euclidean method yielded the highest accuracy in predicting independent test samples and thus clearly outperformed the QDA and Mahalanobis algorithm DA method. It was also determined that the ink type Carbon black had higher CA values than the ink type Black colorant. This work demonstrated the special ability of FT-NIR spectroscopy in combination with DA to examine inkjet-printed documents in a fast and non-destructive fashion. [ABSTRACT FROM AUTHOR]