School of Electrical and Electronic Engineering , Yonsei University , 50 Yonsei-ro , Seodaemun-gu, Seoul 03722 , Republic of Korea.
Center for Mechanical Metrology , Korea Research Institute of Standards and Science , 267 Gajeong-ro , Yuseong-gu, Daejeon 34113 , Republic of Korea.
ACS Nano. 2019 Mar 26;13(3):3023-3030. doi: 10.1021/acsnano.8b07995. Epub 2019 Feb 21.
Large-area, ultrathin flexible tactile sensors with conformal adherence are becoming crucial for advances in wearable electronics, electronic skins and biorobotics. However, normal passive tactile sensors suffer from high crosstalk, resulting in inaccurate sensing, which consequently limits their use in such advanced applications. Active-matrix-driven tactile sensors could potentially overcome such hurdles, but it demands the high performance and reliable operations of the thin-film-transistor array that could efficiently control integrated pressure gauges. Herein, we utilized the benefit of the semiconducting and mechanical excellence of MoS and placed it between high- k AlO dielectric sandwich layers to achieve the high and reliable performance of MoS-based back-plane circuitry and strain sensor. This strategical combination reduces the fabrication complexity and enables the demonstration of an all MoS-based large area (8 × 8 array) active-matrix tactile sensor offering a wide sensing range (1-120 kPa), sensitivity value (Δ R/ R: 0.011 kPa), and a response time (180 ms) with excellent linearity. In addition, it showed potential in sensing multitouch accurately, tracking a stylus trajectory, and detecting the shape of an external object by grasping it using the palm of the human hand.
大面积、超薄、具有良好贴合性的柔性触觉传感器对于可穿戴电子设备、电子皮肤和生物机器人的发展至关重要。然而,普通的无源触觉传感器存在较高的串扰,导致传感不准确,这限制了它们在这些先进应用中的使用。主动矩阵驱动的触觉传感器可能会克服这些障碍,但它需要薄膜晶体管阵列的高性能和可靠运行,该阵列可以有效地控制集成压力计。在这里,我们利用 MoS 的半导体和机械卓越性能的优势,将其置于高 k AlO 介电夹层之间,以实现基于 MoS 的背板电路和应变传感器的高性能和可靠性能。这种策略性的组合降低了制造复杂性,并展示了一种基于全部 MoS 的大面积(8×8 阵列)主动矩阵触觉传感器,该传感器具有较宽的传感范围(1-120 kPa)、灵敏度值(Δ R/R:0.011 kPa)和响应时间(180 ms),具有出色的线性度。此外,它还具有准确感应多指触摸、跟踪手写笔轨迹以及通过用手掌抓取外部物体来检测其形状的潜力。