Fully printed non-contact touch sensors based on GCN/PDMS composites: enabling over-the-bottom detection, 3D recognition, and wireless transmission.

IF 7.4 3区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Science and Technology of Advanced Materials Pub Date : 2024-01-29 eCollection Date: 2024-01-01 DOI:10.1080/14686996.2024.2311635
Bingxiang Li, Xianbin Zheng, SeHyun Kim, Xuhao Wang, Fuhao Jiang, Rong Li, Sang Woo Joo, Chenhao Cong, Xinlin Li
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Abstract

  The rapid advancement in intelligent bionics has elevated electronic skin to a pivotal component in bionic robots, enabling swift responses to diverse external stimuli. Combining wearable touch sensors with IoT technology lays the groundwork for achieving the versatile functionality of electronic skin. However, most current touch sensors rely on capacitive layer deformations induced by pressure, leading to changes in capacitance values. Unfortunately, sensors of this kind often face limitations in practical applications due to their uniform sensing capabilities. This study presents a novel approach by incorporating graphitic carbon nitride (GCN) into polydimethylsiloxane (PDMS) at a low concentration. Surprisingly, this blend of materials with higher dielectric constants yields composite films with lower dielectric constants, contrary to expectations. Unlike traditional capacitive sensors, our non-contact touch sensors exploit electric field interference between the object and the sensor's edge, with enhanced effects from the low dielectric constant GCN/PDMS film. Consequently, we have fabricated touch sensor grids using an array configuration of dispensing printing techniques, facilitating fast response and ultra-low-limit contact detection with finger-to-device distances ranging from 5 to 100 mm. These sensors exhibit excellent resolution in recognizing 3D object shapes and accurately detecting positional motion. Moreover, they enable real-time monitoring of array data with signal transmission over a 4G network. In summary, our proposed approach for fabricating low dielectric constant thin films, as employed in non-contact touch sensors, opens new avenues for advancing electronic skin technology.

基于 GCN/PDMS 复合材料的全印刷非接触式触摸传感器:实现底部检测、三维识别和无线传输。
智能仿生学的飞速发展使电子皮肤成为仿生机器人的重要组成部分,能够对各种外部刺激做出快速反应。将可穿戴式触摸传感器与物联网技术相结合,为实现电子皮肤的多功能性奠定了基础。然而,目前大多数触摸传感器都依赖于压力引起的电容层变形,从而导致电容值发生变化。遗憾的是,这类传感器在实际应用中往往因传感能力单一而受到限制。本研究提出了一种新方法,即在聚二甲基硅氧烷(PDMS)中加入低浓度的石墨氮化碳(GCN)。出乎意料的是,这种具有较高介电常数的材料混合物产生的复合薄膜具有较低的介电常数,与预期相反。与传统的电容式传感器不同,我们的非接触式触摸传感器利用了物体与传感器边缘之间的电场干扰,低介电常数的 GCN/PDMS 薄膜增强了其效果。因此,我们利用点胶印刷技术的阵列配置制造了触摸传感器网格,从而实现了快速响应和超低限接触检测,手指到设备的距离从 5 毫米到 100 毫米不等。这些传感器在识别三维物体形状和准确检测位置运动方面具有出色的分辨率。此外,它们还能通过 4G 网络传输信号,对阵列数据进行实时监控。总之,我们提出的用于制造非接触式触摸传感器的低介电常数薄膜的方法,为推动电子皮肤技术的发展开辟了新的途径。
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来源期刊
Science and Technology of Advanced Materials
Science and Technology of Advanced Materials 工程技术-材料科学:综合
CiteScore
10.60
自引率
3.60%
发文量
52
审稿时长
4.8 months
期刊介绍: Science and Technology of Advanced Materials (STAM) is a leading open access, international journal for outstanding research articles across all aspects of materials science. Our audience is the international community across the disciplines of materials science, physics, chemistry, biology as well as engineering. The journal covers a broad spectrum of topics including functional and structural materials, synthesis and processing, theoretical analyses, characterization and properties of materials. Emphasis is placed on the interdisciplinary nature of materials science and issues at the forefront of the field, such as energy and environmental issues, as well as medical and bioengineering applications. Of particular interest are research papers on the following topics: Materials informatics and materials genomics Materials for 3D printing and additive manufacturing Nanostructured/nanoscale materials and nanodevices Bio-inspired, biomedical, and biological materials; nanomedicine, and novel technologies for clinical and medical applications Materials for energy and environment, next-generation photovoltaics, and green technologies Advanced structural materials, materials for extreme conditions.
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