This article proposes an approach for smart monitoring of the life cycle of innovative graphene-haled filters for water remediation in the presence of pollutants. The measurement technique is based on suitable figures of merit that analyze the time variation of the electrical impedance frequency spectrum. The proposed study considers the remediation of two toxic industrial pollutants, such as the acetonitrile and the 2,4-dichlorophenol. The contribution of this article is twofold. The first is the demonstration of a reliable monitoring setup that is able, for the selected use cases, to correlate in real time the behavior of the electrical impedance of the filter to its status, defined as "absence of pollutants" and/or "saturation." The second contribution is the proposal of suitable figures of merit, based on measurement of the impedance frequency spectrum, able to increase the measurement sensitivity and the reliability and to mitigate some sources of uncertainty typically associated with these kinds of setups and measurements. Results show that the proposed graphene-based filters combine very good filtering capability and high sensitivity of the electrical impedance to the considered pollutants. These results suggest further investigations with other pollutants and the potential use of this technique for the predictive maintenance of the water filters in industrial applications, by endowing the graphene filters of smart sensing devices.

Miele, G., Bellucci, S., Cataldo, A., Di Tinno, A., Ferrigno, L., Maffucci, A., et al. (2021). Electrical impedance spectroscopy for real-time monitoring of the life cycle of graphene nanoplatelets filters for some organic industrial pollutants. ??????? it.cilea.surplus.oa.citation.tipologie.CitationProceedings.prensentedAt ??????? IEEE [10.1109/TIM.2021.3089247].

Electrical impedance spectroscopy for real-time monitoring of the life cycle of graphene nanoplatelets filters for some organic industrial pollutants

Micheli L.;
2021-01-01

Abstract

This article proposes an approach for smart monitoring of the life cycle of innovative graphene-haled filters for water remediation in the presence of pollutants. The measurement technique is based on suitable figures of merit that analyze the time variation of the electrical impedance frequency spectrum. The proposed study considers the remediation of two toxic industrial pollutants, such as the acetonitrile and the 2,4-dichlorophenol. The contribution of this article is twofold. The first is the demonstration of a reliable monitoring setup that is able, for the selected use cases, to correlate in real time the behavior of the electrical impedance of the filter to its status, defined as "absence of pollutants" and/or "saturation." The second contribution is the proposal of suitable figures of merit, based on measurement of the impedance frequency spectrum, able to increase the measurement sensitivity and the reliability and to mitigate some sources of uncertainty typically associated with these kinds of setups and measurements. Results show that the proposed graphene-based filters combine very good filtering capability and high sensitivity of the electrical impedance to the considered pollutants. These results suggest further investigations with other pollutants and the potential use of this technique for the predictive maintenance of the water filters in industrial applications, by endowing the graphene filters of smart sensing devices.
IEEE
2021
Rilevanza internazionale
contributo
2021
Settore CHIM/01 - CHIMICA ANALITICA
English
Electrical impedance spectroscopy (EIS); environmental remediation; graphene nanoplatelets (GNPs); multifrequency analysis; pollution filters; real-time measurement systems
Intervento a convegno
Miele, G., Bellucci, S., Cataldo, A., Di Tinno, A., Ferrigno, L., Maffucci, A., et al. (2021). Electrical impedance spectroscopy for real-time monitoring of the life cycle of graphene nanoplatelets filters for some organic industrial pollutants. ??????? it.cilea.surplus.oa.citation.tipologie.CitationProceedings.prensentedAt ??????? IEEE [10.1109/TIM.2021.3089247].
Miele, G; Bellucci, S; Cataldo, A; Di Tinno, A; Ferrigno, L; Maffucci, A; Micheli, L; Sibilia, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/292149
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