Journal
ACS APPLIED MATERIALS & INTERFACES
Volume -, Issue -, Pages -Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsami.2c12240
Keywords
pressure sensor; wearable electronics; physiological signal monitoring; carbon nanotube self-diffusion; ultrahigh sensitivity; sandwich-like structure
Funding
- National Natural Science Foundation of China [12072189]
- Medicine and Engineering Interdisciplinary Research Fund of Shanghai Jiao Tong University [YG2021QN132]
- Center for Advanced Electronic Materials and Devices (AEMD) of Shanghai Jiao Tong University
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This study proposes a method to improve the performance of wearable sensors by combining the spraying and self-diffusion process of carbon nanotubes. The obtained sensor demonstrates high sensitivity, ultrawide pressure detection range, exceptional durability, fast response, stability, and full flexibility. It shows promising application prospects in the fields of intelligent medical health and motion sensing.
High-performance wearable sensors are required for applications in medical health and human-machine interaction, but their application has limited owing to the trade-off between sensitivity, pressure range, and durability. Herein, we propose the combined spraying and self-diffusion process of carbon nanotubes (CNTs) to balance and improve these parameters with the CNTs spontaneously diffusing into the film surface before the film curing. The obtained sensor not only achieves high sensitivity (155.54 kPa(-1)) and ultrawide pressure detection range (0.1-500 kPa) but also exhibits exceptional durability (over 12,000 pressure cycles at a high pressure of 300 kPa). In addition, the sensor exhibits a fast response (25 ms), good stability, and full flexibility. This process is a general approach that may improve the performance of various types of thin film piezoresistive sensors. Besides, the fabricated sensors can be flexibly scaled into sensor arrays and communicate with smart devices to achieve wireless smart monitoring. At present, the sensor shows broad application prospects in the fields of intelligent medical health and motion sensing.
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