成果简介
柔性应变传感器凭借其轻量、可贴合、实时监测等优势，在可穿戴健康监测与水下软体机器人感知中展现出巨大潜力。然而，碳基柔性传感器在变形过程中导电通路易发生失控断裂，在水下环境中更面临液体干扰导致的电阻波动。因此，开发兼具可控机电转导与水下界面防护的柔性传感器具有重要意义。基于此，本文，吉林大学 刘燕教授团队在《ACS Applied Nano Materials》发表名为”Diving-Bell-Spider-Inspired Superhydrophobic Graphene/CNT–Polyurethane Composite for Underwater Strain Sensing”的论文，研究提出了一种受潜水钟蜘蛛启发、具周期性狭缝结构的超疏水石墨烯/CNT–聚氨酯复合应变传感器（BDBS）。该传感器以激光图案化多孔聚氨酯（PU）骨架为基底，通过石墨烯构建二维导电区、碳纳米管（CNT）桥接相邻富石墨烯域，并以 PDMS 修饰粗糙表面形成超疏水拒水界面。
此外，激光图案化狭缝结构将变形局域在预设狭缝区，调控导电通路的分离与重连；石墨烯二维导电区与一维 CNT 桥接的协同作用，在变形过程中维持了部分导电连续性。经狭缝导向变形、导电网络演化与界面防护三者耦合，该 BDBS 传感器表现出 77.09 的应变因子（GF）、150/175 ms 的响应/恢复时间，并可稳定工作超过 10,000 次循环。同时，该传感器还可实现人体运动监测与水下机器鲨运动模式的区分，使其适用于潮湿及水下环境的可靠软体感知。本研究提出了一种仿生材料设计策略，将机械调控的导电网络演化与水下拒水界面防护相耦合，该策略显著增强了柔性传感器在水下环境中的可靠性，并为相关软物质水下感知系统提供了新的思路。
图文导读
Figure 1.Bioinspired design, working mechanism, and representative underwater applications of the diving-bell-spider-inspired superhydrophobic strain sensor. (a) Bioinspired design based on the diving bell spider (Argyroneta aquatica), highlighting the underwater air layer and slit-based mechanosensory features. The diving-bell-spider image was adapted from ref (30) under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Copyright 2023 The Author(s). The schematic illustration on the right was created by the authors to conceptually represent the bioinspired slit structure. (b) Structural design of the artificial slit-structured sensor, consisting of periodically arranged blocks and gaps on a porous polyurethane (PU) substrate coated with a graphene/CNT conductive network. (c) Fabrication process, including laser engraving of the PU sponge to form periodic slit structures and subsequent PDMS modification to obtain a superhydrophobic surface. (d) Piezoresistive sensing mechanism based on deformation-induced contact-state variation of the graphene/CNT conductive network. (e) Schematic illustration of the superhydrophobic interfacial protection effect at the solid–water interface. (f) Comparison of gauge factor (GF) and cycling durability with previously reported biomimetic strain sensors. (g) Schematic illustration of potential underwater application scenarios, including underwater survey, marine organism tracking, human motion monitoring, and emergency rescue.
Figure 2.Fabrication and multiscale conductive-network characterization of the BDBS. (a) Schematic illustration of the fabrication process, including preparation of the graphene/CNT dispersion, laser engraving of the PU sponge to form periodic slit structures, dip coating, and drying. (b) XRD patterns of pristine PU foam, BDBS, and graphene. (c) FTIR spectra of pristine PU foam and BDBS. (d) Raman spectra of pristine PU foam, BDBS, and graphene. (e) SEM morphology of a representative predefined millimeter-scale laser-patterned slit. (f, g) SEM images showing carbon-nanomaterial-coated regions on the external surface and internal skeleton of the PU scaffold, supporting the formation of a multiscale graphene/CNT conductive network. (h) EDS elemental mapping of the BDBS.
Figure 3.Superhydrophobic interfacial protection, self-cleaning behavior, and breathability of the BDBS. (a) Water contact angles of BDBS samples with different PDMS contents. (b) Time-dependent water-droplet morphology on the optimized BDBS surface. (c) Dynamic droplet contact and detachment test showing the low-adhesion wetting state. (d) Photographs of different liquid droplets on the BDBS surface. (e) Schematic illustration of the water-repellent interfacial state on the PDMS-modified porous surface. (f) Self-cleaning process of the BDBS surface after contamination with solid particles. (g) Experimental setup for water vapor permeability tests using water-containing vials covered with different materials. (h) Water-content variation as a function of time at 25 °C and 50% relative humidity.
Figure 4.Electromechanical sensing performance of the BDBS under tensile deformation. (a) Relative resistance changes of sensors with different slit ratios under tensile strain from 0 to 35%. (b) Relative resistance change and gauge factors of the sensor with a slit ratio of 1/2 under tensile strain up to 35%. (c) Stepwise resistance response under 0–15% tensile strain. (d) Resistance response to small strain increments. (e) Cyclic resistance responses under small strains of 1.0%, 1.8%, 2.6%, and 3.4%. (f) Cyclic resistance responses under larger strains of 5%, 12.5%, and 20%. (g) Resistance responses under a fixed strain at different stretching rates. (h) LED brightness variation when the BDBS is used as a conductive element under loading. (i) Response and recovery times measured under 5% strain. (j) Cycling stability over 10,000 tensile–release cycles under 5% strain.
Figure 5.Piezoresistive mechanism and underwater sensing demonstrations of the BDBS. (a) Equivalent resistance model of the slit-structured BDBS. (b) Equivalent circuit diagram showing segment resistance and contact/interface resistance. (c) Schematic illustration of the strain-dependent evolution of conductive pathways in the graphene/CNT-coated PU network, showing progressive contact loss and partial pathway disconnection from the initial state to small and large strains. (d) Optical images of the BDBS under different stretching states. (e) Schematic illustration of underwater wireless sensing applications. (f) Optical image of the robotic shark in water. (g) Schematic illustration of two BDBS sensors mounted bilaterally on the robotic shark, corresponding to Channel 1 and Channel 2. (h) Two-channel resistance responses of the robotic shark during forward, leftward, and rightward swimming. (i) Resistance responses of BDBS sensors attached to different fingers during hand gestures in air and underwater environments; the top panels show the corresponding hand gestures.
小结
总而言之，通过结合周期性狭缝引导变形、混合导电网络以及疏水界面保护，开发了一种受潜水钟蜘蛛启发的超疏水石墨烯/碳纳米管–聚氨酯复合应变传感器。激光图案化狭缝结构将应变局限于预定义区域内，并调控导电路径的分离与重新连接，而非仅依赖于随机网络中断。在多孔聚氨酯（PU）支架内，石墨烯提供了扩展的导电区域，而碳纳米管（CNT）则在相邻的富石墨烯区域之间架设了连接通道。经聚二甲基硅氧烷（PDMS）改性的粗糙表面进一步限制了液体对导电骨架的直接干扰。通过这种结构与界面相结合的设计，该“潜水钟蜘蛛”（BDBS）应变传感器展现出77.09的应变系数、150/175毫秒的响应/恢复时间，并在超过10,000个循环中保持稳定运行。BDBS 还能实现人体动作监测以及水下机器人鲨鱼运动模式的区分，展示了其在可穿戴和水下传感场景中的实际应用价值。更广泛地说，这项工作提供了一种潜在的仿生材料设计策略，该策略将缝隙引导的导电网络调控与疏水界面保护相结合，以实现水环境中的可靠柔性传感。
文献：https://doi.org/10.1021/acsanm.6c03431
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