Electrical Impedance Spectroscopy for Real-Time Monitoring of the Life Cycle of Graphene Nanoplatelets Filters for Some Organic Industrial Pollutants Article Swipe
Gianfranco Miele
,
Stefano Bellucci
,
Antonino Cataldo
,
Alessio Di Tinno
,
Luigi Ferrigno
,
Antonio Maffucci
,
Laura Micheli
,
S. Sibilia
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/tim.2021.3089247
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/tim.2021.3089247
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.
Related Topics
Concepts
Electrical impedance
Pollutant
Dielectric spectroscopy
Sensitivity (control systems)
Figure of merit
Graphene
Filter (signal processing)
Materials science
Computer science
Electronic engineering
Environmental science
Electrical engineering
Engineering
Optoelectronics
Nanotechnology
Electrode
Chemistry
Physical chemistry
Organic chemistry
Electrochemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tim.2021.3089247
- https://ieeexplore.ieee.org/ielx7/19/9259274/09454515.pdf
- OA Status
- hybrid
- Cited By
- 12
- References
- 34
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3171274529
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3171274529Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tim.2021.3089247Digital Object Identifier
- Title
-
Electrical Impedance Spectroscopy for Real-Time Monitoring of the Life Cycle of Graphene Nanoplatelets Filters for Some Organic Industrial PollutantsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-01Full publication date if available
- Authors
-
Gianfranco Miele, Stefano Bellucci, Antonino Cataldo, Alessio Di Tinno, Luigi Ferrigno, Antonio Maffucci, Laura Micheli, S. SibiliaList of authors in order
- Landing page
-
https://doi.org/10.1109/tim.2021.3089247Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/19/9259274/09454515.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/19/9259274/09454515.pdfDirect OA link when available
- Concepts
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Electrical impedance, Pollutant, Dielectric spectroscopy, Sensitivity (control systems), Figure of merit, Graphene, Filter (signal processing), Materials science, Computer science, Electronic engineering, Environmental science, Electrical engineering, Engineering, Optoelectronics, Nanotechnology, Electrode, Chemistry, Physical chemistry, Organic chemistry, ElectrochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
12Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 3, 2023: 4, 2022: 3, 2021: 1Per-year citation counts (last 5 years)
- References (count)
-
34Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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