A Wearable Fiber Sensor Employing MXene/In <sub>2</sub> O <sub>3</sub> Composites for NH <sub>3</sub> Detection in Kidney Disease Diagnosis
Abstract Continuous and reliable monitoring of ammonia (NH 3 ) biomarkers in exhaled breath holds critical significance for the diagnosis of kidney diseases. However, existing NH 3 sensors often suffer from interference by ambient water molecules, limiting their applications in monitoring exhaled breath with high humidity. In this work, a water‐vapor‐assisted sensing mechanism is proposed, and a humidity‐enhanced flexible NH 3 sensor capable of detecting NH 3 at concentrations as low as 250 ppb in exhaled breath is developed. By integrating hydrothermally synthesized indium oxide (In 2 O 3 ) nanoparticles with delaminated monolayer MXene (Ti 3 C 2 ) nanosheets, a stable heterojunction structure is constructed, which underpins the sensor's performance. Through a streamlined integration strategy, the MXene/In 2 O 3 composite is combined with cotton fibers to fabricate a flexible and wearable NH 3 sensor. This device demonstrates superior gas‐sensing characteristics under ambient temperature and high‐humidity conditions, yielding a response of 70.64% and a response time of 178 s. Furthermore, the flexible sensor is embedded into a KN95 mask to develop an intelligent breath analysis system. By applying machine learning algorithms to model and classify breath samples, a detection accuracy of 94% in real‐world clinical testing is achieved. These results underscore the sensor's substantial potential for non‐invasive early screening and home‐based diagnosis of kidney diseases.
Authors
- Donghang Li (ORCID: https://orcid.org/0000-0002-2607-7968)
- Xi Yang (ORCID: https://orcid.org/0000-0002-4250-3955)
- Junyi Li (ORCID: https://orcid.org/0000-0001-7830-490X)
- Shuo Li (ORCID: https://orcid.org/0000-0002-5184-3230)
- Xiaohong Li (ORCID: https://orcid.org/0000-0003-4178-4051)
- Lijuan Xie
- Ziyao Wang
Institutions
- Southwest University of Science and Technology (CN)
- Tiangong University (CN)
- China Academy of Engineering Physics (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1002/adfm.202524182
- Primary Topic
- Gas Sensing Nanomaterials and Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.00