Environment-Resilient Graphene Vibrotactile Sensitive Sensors for Machine Intelligence,ACS Materials Letters

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Environment-Resilient Graphene Vibrotactile Sensitive Sensors for Machine Intelligence
ACS Materials Letters ( IF 9.6 ) Pub Date : 2020-07-20 , DOI: 10.1021/acsmaterialslett.0c00160
Haicheng Yao ₁ , Pengju Li ₁ , Wen Cheng ₁ , Weidong Yang ₁ , Zijie Yang ₁ , Hashina Parveen Anwar Ali ₁ , Hongchen Guo ₂ , Benjamin C. K. Tee _{1,

3,

4,

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Affiliation

Skin-like sensors that transduce tactile pressures and vibrations with minimal environment variation on performance are crucial in robotic sensing and prosthetic skins. However, sensor performance variations under varying environmental conditions, such as temperature and humidity, are common in piezoresistive sensors because of their intrinsic materials properties. Moreover, the viscoelasticity of soft elastomers causes strain response in a time-dependent fashion, which poses sensor limitations in high-frequency tactile tasks, such as texture recognition. In this work, we demonstrate a new environment-robust tactile sensor via an interfacial engineering process for uniform graphene coating on microstructured elastomers. The sensor enables reliable pressure response over a range of temperature (25–60 °C) and humidity (30–90% relative humidity) conditions, with resistance variations less than 5% and 3%, respectively. It is also able to detect vibrations with frequency up to 1500 Hz. Moreover, our sensor shows ultra-high durability, with high sensitivity and low hysteresis preserved after 1 million cycles. We demonstrate applications with the sensor in epidermal signal monitoring at different arteries, as well as accurate (>95%) surface texture recognition in combination with machine learning.

中文翻译：

用于机器智能的耐环境石墨烯触感敏感传感器

像皮肤一样的传感器能够以最小的环境变化来传递触觉压力和振动，这对于机器人感应和假肢皮肤至关重要。然而，由于其固有的材料特性，在压阻传感器中，温度和湿度等变化的环境条件下的传感器性能变化是常见的。此外，软弹性体的粘弹性导致时间响应方式的应变响应，这在高频触觉任务（例如纹理识别）中造成传感器限制。在这项工作中，我们通过界面工程工艺演示了一种新型的环境稳健的触觉传感器，用于在微结构弹性体上均匀地涂覆石墨烯。该传感器可在一定温度范围（25–60°C）和湿度（相对湿度30–90％）范围内实现可靠的压力响应，电阻变化分别小于5％和3％。它还能够检测频率高达1500 Hz的振动。此外，我们的传感器表现出超高的耐用性，在一百万次循环后保留了高灵敏度和低滞后性。我们展示了传感器在不同动脉的表皮信号监测中的应用，以及结合机器学习的准确（> 95％）表面纹理识别。

更新日期：2020-08-03

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