Dataset Information

Capacitive NO₂ Detection Using CVD Graphene-Based Device.

ABSTRACT: A graphene-based capacitive NO₂ sensing device was developed by utilizing the quantum capacitance effect. We have used a graphene field-effect transistor (G-FET) device whose geometrical capacitance is enhanced by incorporating an aluminum back-gate electrode with a naturally oxidized aluminum surface as an insulating layer. When the graphene, the top-side of the device, is exposed to NO₂, the quantum capacitance of graphene and, thus, the measured capacitance of the device, changed in accordance with NO₂ concentrations ranging from 1-100 parts per million (ppm). The operational principle of the proposed system is also explained with the changes in gate voltage-dependent capacitance of the G-FET exposed to various concentrations of NO₂. Further analyses regarding carrier density changes and potential variances under various concentrations of NO₂ are also presented to strengthen the argument. The results demonstrate the feasibility of capacitive NO₂ sensing using graphene and the operational principle of capacitive NO₂ sensing.

SUBMITTER: Ju W

PROVIDER: S-EPMC9863439 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Capacitive NO2 Detection Using CVD Graphene-Based Device.

Ju Wonbin W Lee Sungbae S

Nanomaterials (Basel, Switzerland) 20230105 2

A graphene-based capacitive NO2 sensing device was developed by utilizing the quantum capacitance effect. We have used a graphene field-effect transistor (G-FET) device whose geometrical capacitance is enhanced by incorporating an aluminum back-gate electrode with a naturally oxidized aluminum surface as an insulating layer. When the graphene, the top-side of the device, is exposed to NO2, the quantum capacitance of graphene and, thus, the measured capacitance of the device ...[more]

PMID: 36677996

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Project description:SARS-CoV-2 virus induced CoVID-19 pandemic has accelerated the development of diagnostic tools. Devices integrated with electrochemical biosensors may be an interesting alternative to respond to the high demand for testing, particularly in contexts where access to standard detection technologies is lacking. Aptamers as recognition elements are useful due to their stability, specificity, and sensitivity to binding target molecules. We have developed a non-invasive electrochemical aptamer-based biosensor targeting SARS-CoV-2 in human saliva. The aptamer is expected to detect the Spike protein of SARS-CoV-2 wildtype and its variants. Laser-induced graphene (LIG) electrodes coated with platinum nanoparticles were biofunctionalized with a biotin-tagged aptamer. Electrochemical Impedance Spectroscopy (EIS) for BA.1 sensing was conducted in sodium chloride/sodium bicarbonate solution supplemented with pooled saliva. To estimate sensing performance, the aptasensor was tested with contrived samples of UV-attenuated virions from 10 to 10,000 copies/ml. Selectivity was assessed by exposing the aptasensor to non-targeted viruses (hCoV-OC43, Influenza A, and RSV-A). EIS data outputs were further used to select a suitable response variable and cutoff frequency. Capacitance increases in response to the gradual loading of the attenuated BA.1. The aptasensor was sensitive and specific for BA.1 at a lower viral load (10-100 copies/ml) and was capable of discriminating between negative and positive contrived samples (with strain specificity against other viruses: OC43, Influenza A, and RSV-A). The aptasensor detected SARS-CoV-2 with an estimated LOD of 1790 copies/ml in contrived samples. In human clinical samples, the aptasensor presents an accuracy of 72%, with 75% of positive percent of agreement and 67% of negative percent of agreement. Our results show that the aptasensor is a promising candidate to detect SARS-CoV-2 during early stages of infection when virion concentrations are low, which may be useful for preventing the asymptomatic spread of CoVID-19.

Dataset Information

Capacitive NO₂ Detection Using CVD Graphene-Based Device.

Publications

Capacitive NO<sub>2</sub> Detection Using CVD Graphene-Based Device.

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