Functionalized carbon nanotubes enabled flexible and scalable CO2 sensors
Year: 2023
Type: article
Abstract: The demand for CO2 detection steadily increases mainly due to the greenhouse effect caused by CO2 emission, which significantly impacts the environment. Among different promising candidates, carbon-based (i.e., graphene, carbon nanotubes, carbon nanoparticles, etc.) composites have been widely studied due to their exceptional mechanical, electrical, and thermal properties. Carbon-based composites also offer high strength-to-weight ratios, excellent conductivity, and superior thermal stability, making them ideal materials for various industrial applications. Despite tremendous efforts to develop CO2 sensors from these materials, obtaining a well-dispersed system that is affordable and easy to use remains challenging. In this work, we have demonstrated a low-cost and effective chemiresistive CO2 sensor based on a composite of functionalized carbon nanotubes (f-CNTs) with polyethyleneimine (PEI). When modified with pyrene and chlorosulfonic acid, the resultant f-CNTs have outstanding dispersibility in PEI, which is mainly attributed to the non-covalent bonds between the CNTs and pyrene and the interaction between the amine and sulfonate groups. The rheology of the f-CNT/PEI composites has been thoroughly studied, which tremendously influences the screen-printing quality. The resulting sensor shows excellent selectivity and sensitivity, which can respond to the CO2 concentration in a wide range of 300 - 5000 ppm. The effects of ink dilution and humidity from the environment on the sensor performance have also been further explored. More importantly, the working mechanism has been proposed, and we hope it can provide insight and a new pathway for future sensor design.
Source: Carbon Trends
Institutions: Brewer Science (United States), Missouri State University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,500
Award: G4962947943
OpenAlex ID: W4386192531
