Scalable Fabrication of Bioinspired Flexible Sensor with Gradient Modulus and Conductivity for Intelligent Gait Recognition

Abstract Flexible pressure sensors hold significant promise in wearable health monitoring due to their superior conformability and mechanical adaptability. However, conventional designs often struggle to achieve both high sensitivity and a wide detection range simultaneously. Herein, inspired by biological gradient structures, a scalable polymer molding method that combines non‐isothermal extrusion compression molding and chemical etching is proposed for fabricating thermoplastic polyurethane (TPU)/carbon nanotubes (CNTs)/carbon black (CB) pressure sensors with gradient modulus and conductivity. Gradient‐oriented pores and CNTs distributions are formed via gradient temperature and shear fields during the extrusion compression molding process, enabling synergistic gradient modulus and conductivity distribution. As expected, the as‐prepared mechanical‐electrical dual‐gradient TPU/CNTs/CB pressure sensor has a dual piezoresistance effect with both positive and negative piezoresistance, exhibiting an ultra‐wide working range (1.5 MPa) and high sensitivity (1.25 kPa −1 ). Furthermore, the TPU/CNTs/CB foam also exhibits exceptional triboelectric sensitivity (1.69 V kPa −1 ). Consequently, the mechanical‐electrical dual‐gradient TPU/CNTs/CB foam is assembled into a system of self‐generated electrical sensing and piezoresistive sensing for recognizing different gaits assisted by machine learning algorithms. The proposed scalable fabrication method and structure‐function synergy offer a promising pathway for next‐generation intelligent sensing technologies.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-07-18
DOI
https://doi.org/10.1002/adfm.202512249
Citations
8
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
5.39

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article

Scalable Fabrication of Bioinspired Flexible Sensor with Gradient Modulus and Conductivity for Intelligent Gait Recognition

Mengman Weng, Kang‐Wei Xia, Jinping Qu, Ting Wu et al.
8 citations
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
5.39
article

Scalable Fabrication of Bioinspired Flexible Sensor with Gradient Modulus and Conductivity for Intelligent Gait Recognition

Mengman Weng, Kang‐Wei Xia, Jinping Qu, Ting Wu, Zan Huang, Qing-wen Yuan, Rui Liu, Zhenyu Gao
article en
8 citations

Abstract

Abstract Flexible pressure sensors hold significant promise in wearable health monitoring due to their superior conformability and mechanical adaptability. However, conventional designs often struggle to achieve both high sensitivity and a wide detection range simultaneously. Herein, inspired by biological gradient structures, a scalable polymer molding method that combines non‐isothermal extrusion compression molding and chemical etching is proposed for fabricating thermoplastic polyurethane (TPU)/carbon nanotubes (CNTs)/carbon black (CB) pressure sensors with gradient modulus and conductivity. Gradient‐oriented pores and CNTs distributions are formed via gradient temperature and shear fields during the extrusion compression molding process, enabling synergistic gradient modulus and conductivity distribution. As expected, the as‐prepared mechanical‐electrical dual‐gradient TPU/CNTs/CB pressure sensor has a dual piezoresistance effect with both positive and negative piezoresistance, exhibiting an ultra‐wide working range (1.5 MPa) and high sensitivity (1.25 kPa −1 ). Furthermore, the TPU/CNTs/CB foam also exhibits exceptional triboelectric sensitivity (1.69 V kPa −1 ). Consequently, the mechanical‐electrical dual‐gradient TPU/CNTs/CB foam is assembled into a system of self‐generated electrical sensing and piezoresistive sensing for recognizing different gaits assisted by machine learning algorithms. The proposed scalable fabrication method and structure‐function synergy offer a promising pathway for next‐generation intelligent sensing technologies.

Advanced Functional MaterialsVol. 36(3)
Medical Protective (US), Ministry of Education (IR), Guangzhou Maritime College (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province, Dongguan Science and Technology Bureau
Openalex Percentile: Top 4%
Advanced Sensor and Energy Harvesting Materials
5.39
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