This work was sparked by the reported identification of man-made cellulosic fibers (rayon/viscose) in the marine environment as a major fraction of plastic litter by Fourier transform infrared (FT-IR) transmission spectroscopy and library search. To assess the plausibility of such findings, both natural and man-made fibers were examined using FT-IR spectroscopy. Spectra acquired by transmission microscopy, attenuated total reflection (ATR) microscopy, and ATR spectroscopy were compared. Library search was employed and results show significant differences in the identification rate depending on the acquisition method of the spectra. Careful selection of search parameters and the choice of spectra acquisition method were found to be essential for optimization of the library search results. When using transmission spectra of fibers and ATR libraries it was not possible to differentiate between man-made and natural fibers. Successful differentiation of natural and man-made cellulosic fibers has been achieved for FT-IR spectra acquired by ATR microscopy and ATR spectroscopy, and application of ATR libraries. As an alternative, chemometric methods such as unsupervised hierarchical cluster analysis, principal component analysis, and partial least squares-discriminant analysis were employed to facilitate identification based on intrinsic relationships of sample spectra and successful discrimination of the fiber type could be achieved. Differences in the ATR spectra depending on the internal reflection element (Ge versus diamond) were observed as expected; however, these did not impair correct classification by chemometric analysis. Moreover, the effects of different levels of humidity on the IR spectra of natural and man-made fibers were investigated, too. It has been found that drying and re-humidification leads to intensity changes of absorption bands of the carbohydrate backbone, but does not impair the identification of the fiber type by library search or cluster analysis.

In recent years the scientific community showed an increasing interest for implementing new, rapid, sensitive and cheaper detection methods that are far better than the classical methods of quantification of polycyclic aromatic hydrocarbons (PAHs), especially with the progress in synthesis of nanomaterials that can be successfully used for the design of electrochemical sensors. This review aims to discuss the latest research activities of the last five years regarding the electrochemical sensing for the determination of polycyclic aromatic hydrocarbons (PAHs) from aqueous resources and catchment areas.

The aim of this study was to detect simultaneously four lung cancer biomarkers: CYFRA 21-1, CEA, NSE and HER-1, from blood samples. In order to do that, we have chosen stochastic senosors based on diamond paste matrices modified with different electroactive materials like dextrins and porphyrins, and ones based on three metals like Au, Cu and Ni. The stochastic sensors chosen for the screening tests of blood samples proved to be a good choice for the simultaneous detection of the four biomarkers, reaching low limits of determination of pg mL⁻¹ magnitude order and high sensitivities. One main advantage of the sensors used for the simultaneous detection of the biomarkers is that the samples are analyzed as taken from the patients, without any pretreatment.

New nanostructured materials based on thin films of Cu and Ni deposited on textile material (veil), as well as gold nanostructured microspheres were used for the design of new stochastic sensors. The stochastic sensors were able to detect simultaneously a panel of biomarkers comprising epidermal growth factor receptor, neuron specific enolase, and carcinoembryonic antigen from whole blood samples with high reliabilities – recovery tests higher than 97.00%, with a RSD (%) lower than 0.1%. The stochastic sensors had shown high sensitivities and low determination levels for the detection of the proposed panel of biomarkers making early detection of lung cancer possible by fast screening of whole blood.