Self-Powered Monitoring of Ammonia Using an MXene/TiO2/Cellulose Nanofiber Heterojunction-Based Sensor Driven by an Electrospun Triboelectric Nanogenerator

被引:144
作者
Sardana, Sagar [1 ]
Kaur, Harpreet [1 ]
Arora, Bindiya [1 ]
Aswal, Dinesh Kumar [2 ]
Mahajan, Aman [1 ]
机构
[1] Guru Nanak Dev Univ, Dept Phys, Amritsar 143005, Punjab, India
[2] Bhabha Atom Res Ctr, Hlth Safety & Environm Grp, Mumbai 400085, Maharashtra, India
关键词
self-powered; nanofibers; triboelectric nanogenerator; MXene; cellulose; chemiresistive gas sensor; GAS SENSOR; ROOM-TEMPERATURE; HUMAN MOTION; MXENE; FILMS;
D O I
10.1021/acssensors.1c02388
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Real-time monitoring of harmful gases is of great significance to identify the environmental hazards to people's lives. However, this application scenario requiring low-power consumption, superior sensitivity, portability, and self-driven operation of gas sensors remains a challenge. Herein, an electrospun triboelectric nanogenerator (TENG) is synthesized using highly electronegative and conducting MXene nanofibers (NFs) paired with biodegradable cellulose acetate NFs (CA-NFs) as triboelectric layers, which supports a sufficient power density (similar to 1361 mW/m(2)@2 M Omega) and shows a self-powered ability to operate the chemiresistive gas sensor fabricated in this work, Further, by using cellulose nanofibers (C-NFs) as a substrate, a new kind of MXene/TiO2/C-NFs heterojunction-based sensory component is developed for detection of NH3. This sensor exhibits excellent reproducibility, high selectivity, and sensitivity toward NH3 (1-100 ppm) along with a fast response/recovery time (76 s/62 s) at room temperature. Finally, a monitoring system comprising a TENG-powered sensor, an equivalent circuit, and an LED visualizer has been assembled and successfully demonstrated as a fully self-powered device for NH3 leakage detection. Thus, this work pushes forward the intelligent gas sensing network self-driven by human motion energy, dispensing the external battery dependence for environment monitoring to reduce the possible health effects.
引用
收藏
页码:312 / 321
页数:10
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