4.7 Article

Electrical Impedance Spectroscopy for Real-Time Monitoring of the Life Cycle of Graphene Nanoplatelets Filters for Some Organic Industrial Pollutants

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2021.3089247

Keywords

Electrical impedance spectroscopy (EIS); environmental remediation; graphene nanoplatelets (GNPs); multifrequency analysis; pollution filters; real-time measurement systems

Funding

  1. Italian Ministry of University and Research through the Smart Distributed System Project (program Dipartimenti di Eccellenza 2018-2022),
  2. Project 2D material-based low cost SENSor of aggressive substancEs (2DSENSE)-NATO under the SPS Programme [G5777]
  3. Italian Ministry of University and Research through the Project C4E-Monitoraggio degli sversamenti illegali attraverso l'impiego sinergico di tecnologie avanzate [ARS01_00927]

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This article proposes a method for smart monitoring the life cycle of graphene filters for water remediation in the presence of pollutants. The study considers the remediation of two toxic industrial pollutants and shows that graphene filters have good filtering capability and high sensitivity to pollutants.
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.

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