Abstract: Multiplex detection of emerging pollutants is essential to improve quality control of water treatment plants, which requires portable systems capable of real-time monitoring. In this paper we describe a flexible, dual electrochemical sensing device that detects nonylphenol and paroxetine in tap water samples. The platform contains two voltammetric sensors, with different working electrodes that were either pretreated or functionalized. Each working electrode was judiciously tailored to cover the concentration range of interest for nonylphenol and paroxetine, and square wave voltammetry was used for detection. An electrochemical pretreatment with sulfuric acid on the printed electrode enabled a selective detection of nonylphenol in 1.0-10 x 10(-6) mol L-1 range with a limit of detection of 8.0 x 10(-7) mol L-1. Paroxetine was detected in the same range with a limit of detection of 6.7 x 10(-7) mol L-1 using the printed electrode coated with a layer of carbon spherical shells. Simultaneous detection of the two analytes was achieved in tap water samples within 1 min, with no fouling and no interference effects. The long-term monitoring capability of the dual sensor was demonstrated in phosphate buffer for 45 days. This performance is statistically equivalent to that of high-performance liquid chromatography (HPLC) for water analysis. The dual-sensor platform is generic and may be extended to other water pollutants and clinical biomarkers in real-time monitoring of the environment and health conditions.

Abstract: Electron energy loss spectroscopy (EELS) is an ideal tool to obtain chemical information from nanoscale volumes. Quantification of the experimental spectra however has prevented for a long time access to the available information in a reliable and reproducible way. We present recent advances in model-based quantification of EELS spectra and show that we obtain the best possible precision for a given dataset, as well as remarkably good accuracies when applied to three different materials. The results are shown to be far superior over conventional quantification techniques and could hold a promise for standardless quantification of EELS spectra.