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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Wearable Fiber Sensor Employing MXene/In 2 O 3 Composites for NH 3 Detection in Kidney Disease Diagnosis

Donghang Li, Xi Yang, Junyi Li, Shuo Li et al.
Advanced Functional Materials
Gas Sensing Nanomaterials and Sensors
article

A Wearable Fiber Sensor Employing MXene/In 2 O 3 Composites for NH 3 Detection in Kidney Disease Diagnosis

Donghang Li, Xi Yang, Junyi Li, Shuo Li, Xiaohong Li, Lijuan Xie, Ziyao Wang
article en

Abstract

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.

Advanced Functional Materials
Southwest University of Science and Technology (CN), Tiangong University (CN), China Academy of Engineering Physics (CN), Tsinghua University (CN)
Openalex Percentile: Top 63%
Gas Sensing Nanomaterials and Sensors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.