High‐performance piezoresistive sensors based on transfer‐free large‐area PdSe2 films for human motion and health care monitoring

标度系数 压阻效应 材料科学 制作 基质(水族馆) 光电子学 应变计 柔性电子器件 纳米技术 聚酰亚胺 复合材料 病理 替代医学 地质学 海洋学 图层(电子) 医学
作者
Rui Zhang,Jie Lin,Tao He,Jiafang Wu,Zhuojun Yang,Liwen Liu,Shaofeng Wen,Yimin Gong,Haifeng Lv,Jing Zhang,Yi Yin,Fangjia Li,Changyong Lan,Chun Li
出处
期刊:InfoMat [Wiley]
卷期号:6 (1) 被引量:17
标识
DOI:10.1002/inf2.12484
摘要

Abstract Two‐dimensional transition metal dichalcogenides (TMDs) are needed in high‐performance piezoresistive sensors due to their strong strain‐induced bandgap modification and thereby large gauge factors. However, integrating a conventional high‐temperature chemical vapor deposition (CVD)‐grown TMD with a flexible substrate necessitates a transfer process that inevitably degrades the sensing properties of the TMDs and increases the overall fabrication complexity. We present a high‐performance piezoresistive strain sensor that employs large‐area PdSe 2 films grown directly on polyimide (PI) substrates via plasma‐assisted selenization of a sputtered Pd film. The reliable strain transfer from the substrate to the PdSe 2 film ensures an outstanding strain‐sensing capability of the sensor. Specifically, the sensors have a gauge factor of up to −315 ± 2.1, a response time under 25 ms, a detection limit of 8 × 10 −6 , and an exceptional stability of over 10 4 loading–unloading cycles. By attaching the sensors to the skin surface, we demonstrate their application for measuring physiological parameters in health care monitoring, including motion, voice, and arterial pulse vibration. Furthermore, using the PdSe 2 film sensor combined with deep learning technology, we achieved intelligent recognition of artery temperature from arterial pulse signals with only a 2% difference between predicted and actual temperatures. The excellent sensing performance, together with the advantages of low‐temperature fabrication and simple device structure, make the PdSe 2 film sensor promising for wearable electronics and health care sensing systems. image
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