After working for years on organic materials, e.g., polythiophenes and relevant composites with metal nanoparticles, we shifted our attention to unusual metals, chosen as candidates to effective amperometric sensing on the basis of the atomic structure and crystalline properties. The present contribution aims at proposing an electrode material rarely employed in electroanalysis, namely Ti. We have experimented that the peculiar nature of Ti leads to electrochemical behavior quite different with respect to the conventional electrode materials, including those based on TiO2 (nano)particles. Our work focuses on the determination of strong oxidizing species, namely H2O2 and HClO, and noble metal ions, namely Au(III). Strong oxidizing species are commodity chemicals employed in a number of different industrial processes, in which usually high concentration levels should be monitored. The procedures proposed have been successfully applied also in complex matrices, such as detergent samples. As to Au(III) determination, it also constitutes a crucial tool in order to increase the efficiency of hydrometallurgic processes and of the recovery of precious materials from electronic waste. Ti electrodes allow the determination of dissolved Au species in the presence of other metal ions. In any cases the electrodes exhibit reproducible and repeatable electrochemical responses, even in the presence of high concentration of organic fouling species typical of bio-sorption processes.
The EU FP7 project CUSTOM (Drugs and Precursor Sensing by Complementing Low Cost Multiple Techniques) aims at developing a new sensing system for the detection of drug precursors in gaseous samples, which includes an External Cavity-Quantum Cascade Laser Photo-Acoustic Sensor (EC-QCLPAS) that is in the final step of realisation. Thus, a simulation based on FT-IR literature spectra has been accomplished, where the development of a proper strategy for the design of the composition of the environment, as much as possible realistic and representative of different scenarios, is of key importance. To this aim, an approach based on the combination of signal processing and experimental design techniques has been developed. The gaseous mixtures were built by adding the considered 4 drug precursor (target) species to the gases typically found in atmosphere, taking also into account possible interfering species. These last chemicals were selected considering custom environments (20 interfering chemical species), whose concentrations have been inferred from literature data. The spectra were first denoised by means of a Fast Wavelet Transform-based algorithm; then, a procedure based on a sigmoidal transfer function was developed to multiply the pure components spectra by the respective concentration values, in a way to correctly preserve background intensity and shape, and to operate only on the absorption bands. The noise structure of the EC-QCLPAS was studied using sample spectra measured with a prototype instrument, and added to the simulated mixtures. Finally a matrix containing 5000 simulated spectra of gaseous mixtures was built up.
Alberto Secchi, Anna Maria Fiorello, Massimiliano Dispenza, Sabato D'Auria, Antonio Varriale, Alessandro Ulrici, Renato Seeber, Juho Uotila, Vincenzo Venditto, Paolo Ciambelli, Juan Carlos Antolín, Francesco Colao, Tom Kuusela, Ilkka Tittonen, Päivi Sievilä, Grégory Maisons
A large number of techniques for drug precursors chemical sensing has been developed in the latest decades. These techniques are able to screen and identify specific molecules even at very low concentration in lab environment, nevertheless the objective to build up a system which proves to be easy to use, compact, able to provide screening over a large number of compounds and discriminate them with low false alarm rate (FA) and high probability of detection (POD) is still an open issue. The project CUSTOM, funded by the European Commission within the FP7, deals with stand alone portable sensing apparatus based on multiple techniques, integrated in a complex system with a complimentary approach. The objective of the project is to achieve an optimum trade-off between opposite requirements: compactness, simplicity, low cost, sensitivity, low false alarm rate and selectivity. The final goal is the realization of an optical sensing platform able to detect traces of drug precursors compounds, such as ephedrine, safrole, acetic anhydride and the Benzyl Methyl Keton (BMK). This is reached by implementing two main sensing techniques: the fluorescence enhanced by the use of specially developed Organic macro-molecules, and a spectroscopic technique in Mid-IR optical range. The fluorescence is highly selectivewith respect to the target compounds, because it is based on properly engineered fluorescent proteins which are able to bind the target analytes, as it happens in an 'immune-type' reaction. The spectroscopic technique is based on the Photo-Acoustic effect, enhanced by the use of a widely Tunable Quantum Cascade Laser. Finally, the sensing platform is equipped with an air sampling system including a pre-concentrator module based on a sorption desorption cycles of a syndiotactic polystyrene polymer.
In the frame of the EU project CUSTOM, a new sensor system for the detection of drug precursors in gaseous samples is being developed, which also includes an External Cavity-Quantum Cascade Laser Photo Acoustic Sensor (ECQCLPAS).
In order to define the characteristics of the laser source, the optimal wavenumbers within the most effective 200 cm-1 range in the mid-infrared region must be identified, in order to lead to optimal detection of the drug precursor molecules in presence of interfering species and of variable composition of the surrounding atmosphere. To this aim, based on simulations made with FT-IR spectra taken from literature, a complex multivariate analysis strategy has been developed to select the optimal wavenumbers. Firstly, the synergistic use of Experimental Design and of Signal Processing techniques led to a dataset of 5000 simulated spectra of mixtures of 33 different gases (including the 4 target molecules). After a preselection, devoted to disregard noisy regions due to small interfering molecules, the simulated mixtures were then used to select the optimal wavenumber range, by maximizing the classification efficiency, as estimated by Partial Least Squares – Discriminant Analysis. A moving window 200 cm-1 wide was used for this purpose. Finally, the optimal wavenumber values were identified within the selected range, using a feature selection approach based on Genetic Algorithms and on resampling. The work made will be relatively easily turned to the spectra actually recorded with the newly developed EC-QCLPAS instrument. Furthermore, the proposed approach allows progressive adaptation of the spectral dataset to real situations, even accounting for specific, different environments.
Conference Committee Involvement (7)
Optical Materials and Biomaterials in Security and Defence Systems Technology
10 September 2018 | Berlin, Germany
Optical Materials and Biomaterials in Security and Defence Systems Technology
11 September 2017 | Warsaw, Poland
Optical Materials and Biomaterials in Security and Defence Systems Technology
28 September 2016 | Edinburgh, United Kingdom
Optical Materials and Biomaterials in Security and Defence Systems Technology
23 September 2015 | Toulouse, France
Optical Materials and Biomaterials in Security and Defence Systems Technology
22 September 2014 | Amsterdam, Netherlands
Optical Materials and Biomaterials in Security and Defence Systems Technology X
25 September 2013 | Dresden, Germany
Optical Materials and Biomaterials in Security and Defence Systems Technology
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