ZnSnO3/CNFs flexible pressure sensors based on multi-level microstructure and their high-performance applications
Abstract
Flexible pressure sensors hold extensive application potential in fields such as wearable devices, health monitoring, electronic skin, and human–machine interaction. The enhancement of their performance mainly relies on innovations in sensitive materials and microstructure design. In this paper, the perovskite material ZnSnO3, which possesses an excellent piezoresistive effect, was selected. A film with multilevel microstructures was fabricated through the template-assisted electrospinning technique. This film has protruding microstructures on its surface and a fiber-network structure inside. After heat treatment, a ZnSnO3/CNFs film was obtained. The ZnSnO3/CNFs pressure sensor exhibits outstanding performance, featuring a high sensitivity of −2.55 kPa−1 (0–0.2 kPa), a rapid response/recovery time of 40 ms/39 ms, a wide working range (0–25 kPa), and excellent stability (500 s cycle test). Through equivalent circuit diagram analysis and finite-element simulation, the influence of multilevel microstructures on sensing performance was further investigated. The results indicate that the multilevel microstructures composed of surface-raised microstructures and internal fiber networks significantly enhance the performance of the sensor. In this paper, a pressure signal acquisition and transmission platform was established and applied to human motion monitoring. A 3 × 3 sensor array was fabricated to achieve the recognition of object geometric contours and the precise tracking of surface sliding trajectories. Additionally, the flexible sensors were applied to deep-learning-assisted handwriting recognition. By constructing an intelligent handwritten e-skin, the data collection and feature analysis of handwritten numbers and letters were realized. The ZnSnO3/CNFs pressure sensor fabricated in this paper features good sensitivity, stability, and reliability, thus offering broad application prospects in fields such as wearable devices, human–machine interaction, and intelligent health monitoring.

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