Wireless Flexible System for Highly Sensitive Ammonia Detection Based on Polyaniline/Carbon Nanotubes

Author:

Zhuang Yi1ORCID,Wang Xue1,Lai Pengfei1,Li Jin1,Chen Le1,Lin Yuanjing1,Wang Fei1ORCID

Affiliation:

1. The School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, China

Abstract

Ammonia (NH3) is a harmful atmospheric pollutant and an important indicator of environment, health, and food safety conditions. Wearable devices with flexible gas sensors offer convenient real-time NH3 monitoring capabilities. A flexible ammonia gas sensing system to support the internet of things (IoT) is proposed. The flexible gas sensor in this system utilizes polyaniline (PANI) with multiwall carbon nanotubes (MWCNTs) decoration as a sensitive material, coated on a silver interdigital electrode on a polyethylene terephthalate (PET) substrate. Gas sensors are combined with other electronic components to form a flexible electronic system. The IoT functionality of the system comes from a microcontroller with Wi-Fi capability. The flexible gas sensor demonstrates commendable sensitivity, selectivity, humidity resistance, and long lifespan. The experimental data procured from the sensor reveal a remarkably low detection threshold of 0.3 ppm, aligning well with the required specifications for monitoring ammonia concentrations in exhaled breath gas, which typically range from 0.425 to 1.8 ppm. Furthermore, the sensor demonstrates a negligible reaction to the presence of interfering gases, such as ethanol, acetone, and methanol, thereby ensuring high selectivity for ammonia detection. In addition to these attributes, the sensor maintains consistent stability across a range of environmental conditions, including varying humidity levels, repeated bending cycles, and diverse angles of orientation. A portable, stable, and effective flexible IoT system solution for real-time ammonia sensing is demonstrated by collecting data at the edge end, processing the data in the cloud, and displaying the data at the user end.

Funder

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Publisher

MDPI AG

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