中文版 | English
题名

高灵敏度线性响应离电压力传感技术及其应用研究

其他题名
RESEARCH OF HIGH SENSITIVITY AND LINEARITY IONTRONIC PRESSURE SENSING TECHNOLOGY AND ITS APPLICATION
姓名
姓名拼音
YANG Jing
学号
12031075
学位类型
博士
学位专业
0702 物理学
学科门类/专业学位类别
07 理学
导师
王太宏
导师单位
电子与电气工程系
论文答辩日期
2024-05-09
论文提交日期
2024-06-27
学位授予单位
南方科技大学
学位授予地点
深圳
摘要

皮肤是人体最大的感受器官,皮肤中的机械感受器能够将接触、振动等环境机械刺激转化为电信号,并传递到神经系统,赋予人类识别物体、辨别纹理等精细触觉感知能力。生物机械感受器激发了研究人员对于人工机械感受器(又称柔性压力传感器)的积极探索。柔性压力传感器可以将外界机械刺激转化为电信号,在构建智能机器人触觉、开发具有触觉感知功能的智能假肢、可穿戴医疗设备以及人机交互等领域具有广泛的应用前景。电容型柔性压力传感器结构简单,可以实现对静态力和动态力的响应,因此受到研究人员的广泛关注。但是其响应电容较小,容易受到环境中寄生电容和电磁噪音等的干扰。离电型压力传感器基于界面双电层效应,具有较大的单位面积电容,能够有效抑制环境中电磁噪音的干扰,实现超高的电容响应。本论文围绕离电型压力传感器,从双电层理论模型出发,通过传感机理分析、有限元仿真以及实验论证,系统研究了介电层离子动态约束、电极非平衡压缩以及材料压缩模量调谐三种提高离电压力传感器灵敏度的方法。传感器灵敏度不仅从32.70 kPa−1 成功提高至25,548.24 kPa−1,而且解决了过去高灵敏度和响应线性不兼容的问题,为其在人体生理信号监测、智能机器人手构建等领域的应用提供了有力支持。具体的创新工作如下:
(1)提出了一种离子动态约束传感机制,将离子液体和聚(偏氟乙烯-六氟丙烯) 混合纳米纤维嵌入热塑性聚氨酯基体中,制备得到以核-壳结构离子纳米纤维膜为介电层的离电压力传感器,可以实现应力触发下介电层界面离子的动态约束过程,为模仿生物机械感受器触觉感知过程提供了依据 。该传感器在0.04 Pa-209 kPa 的宽线性压力范围内具有32.70 kPa−1的高灵敏度以及0.035%的超高压力分辨率(预加载压力100 kPa),在生理信号监测、辅助物体识别等领域表现出潜在的应用价值。
(2)建立了一种弯曲引发的非平衡压缩策略,采用具有特殊分支瓣状的直立石墨烯电极,能够有效提高电极微结构的可压缩性,在离电型压力传感器双电层界面面积增长效率方面发挥了关键作用。克服了目前普遍使用的稳定轴向微结构策略(例如微金字塔)在压缩过程中容易出现的结构刚化、灵敏度和线性度不兼容的问题。该离电压力传感器在0.49 Pa-66.67 kPa 的宽压力范围内,实现了高灵敏度(185.09 kPa−1)和高线性度(R2=0.9999)的兼容。并且成功应用于机器人抓取任务中,借助多层感知(MLP)神经网络可以实现对不同材料、形状物体的识别。

(3)提出了一种基于压缩模量的传感器性能调制方法,不仅成功实现了离电压力传感器灵敏度的新突破,还可以根据应用场景的需求对传感器性能进行程式化定制。基于该理论制备的三维多孔石墨烯离电压力传感器展现出25,548.24 kPa−1的超高灵敏度,并且传感器的线性压力范围从15 kPa 到127 kPa 可调。在峰值压力为3.5 kPa 的1000 次加载、卸载循环中,传感器信号漂移小于0.5%。我们使用该传感器开发了一个压力反馈控制机器人手,可以自主调节抓取角度,精确跟踪气球内部的压力变化行为。

从离电型压力传感器的力学感知机理出发,我们设计得到了超高灵敏度、高分辨率的线性响应柔性压力传感器,为复杂场景下的触觉感知的应用开辟了新的机遇。

其他摘要

The skin is the largest sensory organ of the human body. Mechanical receptors within the skin can convert environmental mechanical stimuli such as touch and vibration into electrical signals, which are then transmitted to the nervous system, endowing humans
with the ability to recognize objects, discern textures, and perceive fine tactile sensations. The discovery of biological mechanoreceptors has spurred researchers to actively explore artificial mechanoreceptors, also known as flexible pressure sensors. Flexible pressure sensors have the capability to convert external mechanical stimuli into electrical signals, holding broad prospects for applications in fields such as constructing intelligent robotic touch systems, developing smart prosthetics with tactile sensing capabilities, wearable medical devices, and human-machine interaction. Capacitive flexible pressure sensors, characterized by their simple structure and ability to respond to both static and dynamic forces, have garnered significant attention from researchers. However, they tend to exhibit relatively small capacitance responses and are prone to interference from parasitic capacitance and electromagnetic noise present in the environment. Iontronic pressure sensors, based on the interface electrical double layer effect, possess larger unit-area capacitance, enabling them to effectively suppress interference from electromagnetic noise in the environment and achieve ultra-high capacitance response. This paper revolves around iontronic pressure sensors, through a systematic approach involving analysis of sensing mechanisms, finite element analysis, and experimental verification, three methods to enhance the sensitivity of iontronic pressure sensors are studied. These methods include dynamic ion confinement in the dielectric layer, electrode non-equilibrium compression, and material compressive modulus tuning The sensitivity of the sensor has been successfully increased from 32.70 kPa−1 to 25,548.24 kPa−1, addressing the previous issue of incompatibility between high sensitivity and response linearity. This provides robust support for its applications in fields such as monitoring physiological signals in the human body and constructing intelligent robotic hands.The specific innovative work is as follows:
(1) We propose a dynamic ion confinement sensing mechanism. By embedding a mixture of ionic liquid and poly(vinylidene fluoride-co-hexafluoropropylene) nanofibers
into a thermoplastic polyurethane matrix, a core-shell structured ion nanofiber membrane has been prepared as the dielectric layer of an iontronic pressure sensor. This mechanism enables the dynamic confinement of ions at the interface of the dielectric layer under stress, providing a basis for mimicking the tactile perception process of biological mechanoreceptors.The sensor exhibits a high sensitivity of 32.70 kPa−1 within a wide linear pressure range from 0.04 Pa to 209 kPa, along with an ultra-high pressure resolution of 0.035% (preloading pressure 100 kPa). The sensor demonstrates potential application value in physiological signal monitoring, object recognition assistance, and other fields.

(2) Building upon the dynamic ion confinement within the dielectric layer, we pioneer a curvature-induced non-equilibrium compression strategy. Utilizing vertical graphene electrodes with distinctive branched morphology effectively enhances the compressibility of electrode, playing a crucial role in promoting the efficiency of interface
area growth at the electrical double layer of iontronic pressure sensors. This strategy overcomes the issues of structural stiffening, and incompatibility between sensitivity and linearity, commonly encountered with the prevailing stable axial microstructure strategy (such as micro-pyramids) during the compression process. This pressure sensor achieves high sensitivity (185.09 kPa−1) and excellent linearity (R2=0.9999) compatibility within a wide pressure range from 0.49 Pa to 66.67 kPa. It has been successfully applied in robotic grasping tasks, enabling the recognition of objects with different materials and shapes through Multilayer Perceptron (MLP) neural networks.

(3) We proposea method for modulating the performance of sensors based on compression modulus, which not only achieves a breakthrough in the sensitivity of iontronic pressure sensors but also allows for programmatically tailored sensor performance according to application requirements. Based on this theory, a three-dimensional porous graphene iontronic pressure sensor is fabricated, demonstrating an ultra-high sensitivity of 25,548.24 kPa−1 and an adjustable linear pressure range from 15 kPa to 127 kPa. In 1000 cycles of loading and unloading with a peak pressure of 3.5 kPa, the sensor's signal drift is less than 0.5%. We utilize this sensor to develop a pressure feedback-controlled robotic hand capable of autonomously adjusting grasping angles and accurately tracking pressure variations within balloons.

Starting from the mechanical perception mechanism of iontronic pressure sensors, we have designed ultra-high sensitivity, high-resolution linear response flexible pressure sensors, opening up new opportunities for tactile perception applications in complex scenarios.

关键词
其他关键词
语种
中文
培养类别
独立培养
入学年份
2020
学位授予年份
2024-07
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杨静. 高灵敏度线性响应离电压力传感技术及其应用研究[D]. 深圳. 南方科技大学,2024.
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