Development of a polyaniline-based sensor improved ammonia detection in CKD patients, indicating benefits for health monitoring systems.
With the increasing demand for health monitoring, the early diagnosis of chronic kidney disease (CKD) faces challenges related to insufficient sensitivity, limited selectivity, and humidity interference in current detection methods. Breath sensors targeting ammonia (NH 3 ) have shown significant potential for early CKD diagnosis due to their excellent ability to analyze human breath. However, the rational design of the functional sensing layer—particularly concerning active sites and adhesion forces—remains a considerable challenge. This study developed a multifunctional wearable sensor based on polyaniline (PANI) featuring a bionic rose micro‐dome structure, fabricated via a modified in situ growth method. Owing to the superhydrophobic microstructured sensing layer with a contact angle of 108.6°, the sensor exhibits excellent humidity resistance and an expanded NH 3 contact area. The sensor demonstrates a remarkable 97.3% improvement in response to 100 ppm NH 3 , a low detection limit of 0.1 ppm, and high moisture resistance under 80% relative humidity. Clinical tests reveal its potential for breath monitoring in CKD patients, effectively distinguishing between varying disease stages with an accuracy of up to 91%. Furthermore, due to the specialized nanostructure modification providing strong adhesion, the sensor exhibits a pressure sensitivity of 0.7126 kPa − 1 and a broad detection range of 0–35 000 Pa, thereby enabling precise monitoring of subtle human movements and gestures. This research proposes a novel strategy for designing high‐performance, multifunctional flexible sensors based on PANI microstructures. This approach not only enhances the detection capability of trace NH 3 in complex humidity environments but also offers an innovative solution for the early screening and clinical monitoring of CKD, as well as for the development of multifunctional health monitoring systems.
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Sheng et al. (2026) studied this question.
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