Self-Healing, Laminated, and Low Resistance NH3 Sensor Based on 6,6',6â³-(Nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) Sensing Material Operating at Room Temperature.
ACS Sens
; 9(1): 171-181, 2024 01 26.
Article
em En
| MEDLINE
| ID: mdl-38159288
ABSTRACT
With the rapid development of the concept of the Internet of Things (IoT), gas sensors with the function of simulating the human sense of smell became irreplaceable as a key element. Among them, ammonia (NH3) sensors played an important role in respiration tests, environmental monitoring, safety, and other fields. However, the fabrication of the high-performance device with high stability and resistance to mechanical damages was still a challenge. In this work, polyurethane (PU) with excellent self-healing ability was applied as the substrate, and the sensor was designed from new sensitive material design and device structure optimization, through applying the organic molecule with groups which could absorb NH3 and the laminated structure to shorten the electronic transmission path to achieve a low resistance state and favorable sensing properties. Accordingly, a room temperature flexible NH3 sensor based on 6,6',6â³-(nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) (TPA-3DCNPZ) was successfully developed. The device could self-heal by means of a thermal evaporation assisted method. It exhibited a detection limit of 1 ppm at 98% relative humidity (RH), as well as great stability, selectivity, bending flexibility, and self-healing properties. The improved NH3 sensing performance under high RH was further investigated by complex impedance plots (CIPs) and density functional theory (DFT), attributing to the enhanced adsorption of NH3. The TPA-3DCNPZ based NH3 sensors proved to have great potential for application on simulated exhaled breath to determine the severity of kidney diseases and the progress of treatment. This work also provided new ideas for the construction of high-performance room temperature NH3 sensors.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Materiais Inteligentes
Limite:
Humans
Idioma:
En
Revista:
ACS Sens
Ano de publicação:
2024
Tipo de documento:
Article