Double-sided microstructured flexible iontronic pressure sensor with wide linear sensing range

线性 压力传感器 材料科学 微观结构 棱锥(几何) 光电子学 纳米技术 电子工程 复合材料 光学 机械工程 工程类 物理
作者
Yuan Hao,Qiran Zhang,Yunqi Cheng,Rongyu Xu,Haoran Li,Mengyao Tian,Jinming Ma,Tifeng Jiao
出处
期刊:Journal of Colloid and Interface Science [Elsevier]
卷期号:670: 41-49 被引量:24
标识
DOI:10.1016/j.jcis.2024.05.054
摘要

Iontronic pressure sensors have garnered significant attention for their potential in wearable electronic devices. While simple microstructures can enhance sensor sensitivity, the majority of them predominantly amplify sensitivity at lower pressure ranges and fail to enhance sensitivity at higher pressure ranges, leading to nonlinearity. In the absence of linear sensitivity in a pressure sensor, users are unable to derive precise information from its output, necessitating further signal processing. Hence, crafting a linearity flexible pressure sensor through a straightforward approach remains a formidable task. Herein, a double-sided microstructured flexible iontronic pressure sensor is presented with wide linear sensing range. The ionic gel is made by 1-Ethyl-3-methylimidazolium bis(tri-fluoromethylsulfonyl)imide (EMIM:TFSI) into the matrix of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), which acts as active layer, featuring irregular microstructures (IMS) and pyramid microstructures (PMS) on both sides. Unlike previous complex methods, IMS and uniform PMS are easily and achieved through pattern transfer from a sandpaper mold and micro-pyramid template. The iontronic pressure sensor exhibits exceptional signal linearity with R2 values of 0.9975 and 0.9985, in the wide pressure range from 100 to 760kPa and 760 kPa to 1000 kPa, respectively. This outstanding linearity and wide sensing range stem from a delicate balance between microstructure compression and mechanical alignment at the ionic gel interface. This study provides valuable insights into achieving linear responses by strategically designing microstructures in flexible pressure sensors, with potential applications in intelligent robots and health monitoring.
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