Robust and Biodegradable Heterogeneous Electronics with Customizable Cylindrical Architecture for Interference-Free Respiratory Rate Monitoring

A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness. However, a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations, as well as mechanical motion artifacts. Herein, a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode, featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness, thereby realizing the long-term breath-induced pressure detection. Notably, molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration, driven by shear forces and interfacial interactions, which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer. The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation (0-120°, ~ 2.8 × 10<sup>-3</sup> A) and sensing accuracy without crosstalk (humidity 50%-100% and temperature 30-80 °C). Besides, the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages (average prediction accuracy ~ 90%). It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.

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Publication Details

Journal
Nano-Micro Letters
Published
2025-08-19
DOI
https://doi.org/10.1007/s40820-025-01879-x
Citations
8
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
5.39
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article

Robust and Biodegradable Heterogeneous Electronics with Customizable Cylindrical Architecture for Interference-Free Respiratory Rate Monitoring

Jun He Yang, Zhouyang Hu, Fangqing Wang, Han Zhu et al.
8 citations
Nano-Micro Letters
Advanced Sensor and Energy Harvesting Materials
5.39
article

Robust and Biodegradable Heterogeneous Electronics with Customizable Cylindrical Architecture for Interference-Free Respiratory Rate Monitoring

Jun He Yang, Zhouyang Hu, Fangqing Wang, Han Zhu, Changyou Shao, Pengcheng Fu, Sanwei Hao, Hailin Cong, Jing Zhang, Wenqi Wang, Chao Wang, Yaru Yu
article en
8 citations

Abstract

A rapidly growing field is piezoresistive sensor for accurate respiration rate monitoring to suppress the worldwide respiratory illness. However, a large neglected issue is the sensing durability and accuracy without interference since the expiratory pressure always coupled with external humidity and temperature variations, as well as mechanical motion artifacts. Herein, a robust and biodegradable piezoresistive sensor is reported that consists of heterogeneous MXene/cellulose-gelation sensing layer and Ag-based interdigital electrode, featuring customizable cylindrical interface arrangement and compact hierarchical laminated architecture for collectively regulating the piezoresistive response and mechanical robustness, thereby realizing the long-term breath-induced pressure detection. Notably, molecular dynamics simulations reveal the frequent angle inversion and reorientation of MXene/cellulose in vacuum filtration, driven by shear forces and interfacial interactions, which facilitate the establishment of hydrogen bonds and optimize the architecture design in sensing layer. The resultant sensor delivers unprecedented collection features of superior stability for off-axis deformation (0-120°, ~ 2.8 × 10<sup>-3</sup> A) and sensing accuracy without crosstalk (humidity 50%-100% and temperature 30-80 °C). Besides, the sensor-embedded mask together with machine learning models is achieved to train and classify the respiration status for volunteers with different ages (average prediction accuracy ~ 90%). It is envisioned that the customizable architecture design and sensor paradigm will shed light on the advanced stability of sustainable electronics and pave the way for the commercial application in respiratory monitory.

Nano-Micro LettersVol. 18(1)
Shandong University of Technology (CN), Beijing Forestry University (CN), Dalian Polytechnic University (CN)
Openalex Percentile: Top 4%
Advanced Sensor and Energy Harvesting Materials
5.39
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