4.6 Article

A dual-mode foam sensor employing Ti3C2Tx/In2O3 composites for NH3 detection with memory function and body movement monitoring for kidney disease diagnosis

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JOURNAL OF MATERIALS CHEMISTRY A
卷 11, 期 44, 页码 24299-24310

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ROYAL SOC CHEMISTRY
DOI: 10.1039/d3ta05670h

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A bi-functional sensing platform based on Ti3C2Tx/In2O3 nanocomposites modified TPU foam sensor was constructed for the detection of gas and motion bio-signals of kidney diseases. The developed sensor exhibited the capability to detect NH3 gas as low as 1 ppm and accurately interpret human motion signals.
Research on non-invasive nephropathy testing has been a prominent area of interest both domestically and internationally. However, the conventional NH3 measurement using gas sensors is distorted by other exhaled components, compromising assessment precision. In this study, a bi-functional sensing platform based on Ti3C2Tx/In2O3 nanocomposites modified TPU foam sensor was constructed to realize the detection of gas and motion bio-signals of kidney diseases. By combining surface-functionalized In2O3 nanotubes with Ti3C2Tx nanoflakes, the achieved nanocomposites showed a strong synergistic effect and structural stability. In addition, by depositing Ti3C2Tx/In2O3 nanocomposites onto the TPU foam substrate, the detection of multiple external stimuli with non-interfering in a flexible and room temperature way can be achieved. The developed Ti3C2Tx/In2O3 foam sensor exhibits the capability to detect NH3 gas as low as 1 ppm with memory function, demonstrating its excellent practical utility in complex exhaled environments. Moreover, the sensor displays a remarkable ability to accurately interpret human motion signals, including leg flexion and extension. The Ti3C2Tx/In2O3 foam sensor was successfully deployed for the comprehensive monitoring of abnormal physiological signals in patients with kidney disease, encompassing simulated NH3 exhalation patterns, and limb flexion-extension signals. This study introduces some ideas to develop a multifunctional sensing platform for disease diagnosis in a non-invasive way.

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