Highly Sensitive Piezoresistive Pressure Sensor Based on Super-Elastic 3D Buckling Carbon Nanofibers for Human Physiological Signals' Monitoring.

Zhoujun Pang, Yu Zhao, Ningqi Luo, Dihu Chen, Min Chen

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Article in Nanomaterials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Zhoujun PangState Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510275, China.

Yu ZhaoSchool of Materials and Energy, Guangdong University of Technology, Guangzhou 510006, China.

Ningqi LuoSchool of Materials and Energy, Guangdong University of Technology, Guangzhou 510006, China.

Dihu ChenState Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510275, China.

Min ChenSchool of Physics, Sun Yat-sen University, Guangzhou 510275, China.

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6 · The paper itself

Abstract

The three-dimensional (3D) carbon nanostructures/foams are commonly used as active materials for the high-performance flexible piezoresistive sensors due to their superior properties. However, the intrinsic brittleness and poor sensing properties of monolithic carbon material still limits its application. Rational design of the microstructure is an attractive approach to achieve piezoresistive material with superior mechanical and sensing properties, simultaneously. Herein, we introduce novel three-dimensional buckling carbon nanofibers (3D BCNFs) that feature a unique serpentine-buckling microstructure. The obtained 3D BCNFs exhibit superior mechanical properties, including super-elasticity (recovery speed up to 950 mm s

Indexed as

3D buckling carbon nanofibersflexible piezoresistive sensormechanical propertypiezoresistive sensitivity

Identifiers

PMID35893489

DOI10.3390/nano12152522

PMCPMC9330309

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.