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DOI 10.1021/acssensors.4c03468

Медицинская библиотека · ACS sensors · 2025

Wearable, Breathable, and Wireless Gas Sensor Enables Highly Selective Exhaled Ammonia Detection and Real-Time Noninvasive Illness Diagnosis.

Dong Haipeng, Li Xiaowei, Liu Yu, Cheng Wanying, Han Chaohan, Yin Yunpeng, Li Xinghua, Shao Changlu, Liu Yichun

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Аннотация

Wearable gas sensors capable of real-time analysis of exhaled breath have been identified as ideal devices for noninvasive illness diagnosis. However, due to their inherent rigidity and brittleness, as well as high cross-sensitivity, conventional semiconductor gas sensors face significant challenges in achieving high flexibility, robustness, and selective exhaled breath analysis. Herein, we propose a wearable gas sensor by anchoring a SnS2 nanosheets/polyaniline (PANI) sensing layer in situ onto a permeable and flexible yttria-stabilized zirconia (YSZ) nanofiber substrate for the analysis of exhaled NH3. The cross-linked meshes of the YSZ network and the abundant voids between SnS2 nanosheets effectively release the stress concentration in YSZ/SnS2/PANI films, enabling the sensor to withstand severe folding/bending deformation. The organic PANI sheath endows the YSZ/SnS2/PANI-based gas sensor with enhanced toughness (0.66 kJ·m-3), stable electrical connection, and excellent robustness. The unique protonation/deprotonation sensing mechanism, coupled with the heterojunction effect of the sensing layer, ensures outstanding selectivity (sensor immunity coefficient ≈ 69%) and a high response to NH3. To support wearable applications, the sensing signals from the wearable sensor are transmitted wirelessly via Bluetooth and displayed on a smartphone. This work greatly advances the application of a wearable semiconductor sensor in personal disease diagnosis.

Для цитирования: Dong Haipeng, Li Xiaowei, Liu Yu, Cheng Wanying, Han Chaohan, Yin Yunpeng, Li Xinghua, Shao Changlu, Liu Yichun. Wearable, Breathable, and Wireless Gas Sensor Enables Highly Selective Exhaled Ammonia Detection and Real-Time Noninvasive Illness Diagnosis.. ACS sensors. 2025. DOI: 10.1021/acssensors.4c03468.

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