RESUMO
Since 1940, poly- or perfluorinated alkyl substances (PFAS) have been largely used in many applications, including paints, fire foaming, household items, product packaging, and fabrics. Because of their extremely high persistency, they have been defined as "forever chemicals". Although the EU is taking action to reduce their use, their widespread occurrence in environmental matrices and their harmful effects on human health require the use of highly performing analytical methods for efficient monitoring. Furthermore, novel PFAS are constantly revealed by both EU and National environmental agencies. The objective of this work is to investigate the cause of the signal decrease during the analysis of a standard PFAS mixture in water-based matrices, by proposing an efficient technical procedure for laboratory specialists. The analyses were carried out on a mixture of 30 PFAS, including both regulated and unknown substances (which are expected to be introduced in the guidelines), characterized by different chemical features, using LC-vials of two different materials, namely, glass and polypropylene, and dissolved in two solvents, namely, water and water-methanol. The temperature of analysis and the concentration of PFAS were also considered through LC-MS analyses at different times, in the 0-15 h range. Depending on the chemical structure and length of the PFAS, sampling and treatment procedures may be adopted to tackle the decrease and the release from the containers, reducing the risk of underestimating PFAS also in real water matrices.
RESUMO
This work aimed to develop an easy-to-use smartphone-based electrochemical biosensor to quickly assess a coffee blend's total polyphenols (Phs) content at the industrial and individual levels. The device is based on a commercial carbon-based screen-printed electrode (SPE) modified with multi-walled carbon nanotubes (CNTs) and gold nanoparticles (GNPs). At the same time, the biological recognition element, Laccase from Trametes versicolor, TvLac, was immobilized on the sensor surface by using glutaraldehyde (GA) as a cross-linking agent. The platform was electrochemically characterized to ascertain the influence of the SPE surface modification on its performance. The working electrode (WE) surface morphology characterization was obtained by scanning electron microscopy (SEM) and Fourier-transform infrared (FT-IR) imaging. All the measurements were carried out with a micro-potentiostat, the Sensit Smart by PalmSens, connected to a smartphone. The developed biosensor provided a sensitivity of 0.12 µA/µM, a linear response ranging from 5 to 70 µM, and a lower detection limit (LOD) of 2.99 µM. Afterward, the biosensor was tested for quantifying the total Phs content in coffee blends, evaluating the influence of both the variety and the roasting degree. The smartphone-based electrochemical biosensor's performance was validated through the Folin-Ciocâlteu standard method.
