1成果简介 

　　柔性电子器件的快速发展对各向异性应变传感提出了迫切需求——在软体机器人、人机交互、健康监测等领域，不仅需要感知应变的大小，更需要识别应变的方向。碳纳米管作为典型的一维纳米材料，具有极高的长径比和优异的机电性能，是构建各向异性导电网络的理想选择。当CNTs沿特定方向有序排列时，沿排列方向的导电性远高于垂直方向，从而产生显著的各向异性传感响应。然而，低维纳米材料的可编程精准组装一直是制约各向异性柔性电子发展的长期瓶颈。现有策略面临三大核心挑战：(1) 取向效率低——传统的过滤法、刮涂法、机械拉伸法难以实现高取向度，且耗时较长；(2) 空间可编程性差——难以在微纳尺度上实现CNTs在特定位置、特定方向的精准沉积与图案化；(3) 制备工艺复杂——光刻、模板法等虽然精度高，但工艺繁琐、成本高昂，难以大规模制备。介电电泳（DEP）是指在非均匀电场作用下，中性粒子因极化而产生定向移动的现象。通过设计电极形状和电场分布，DEP可实现纳米材料的空间选择性和取向性沉积，是一种极具潜力的可编程组装技术。然而，传统DEP组装存在电场分布不易调控、组装时间长等问题，限制了其在各向异性传感器件中的应用。

　　本文，西安交通大学Yongsheng Shi、蒋维涛 教授等在《Small Methods》期刊发表名为"Programmable Dielectrophoretic Assembly of Carbon Nanotube Arrays for Multidirectional Strain Sensor"的论文。该研究创新性地提出了可编程介电电泳组装方法，利用结构化电场和锯齿电极实现了碳纳米管的空间选择性、取向性沉积，并构筑了多维应变传感器，实现了应变大小和方向的同步检测。

　　该工作的核心创新在于：(1) 锯齿电极设计——锯齿状电极结构显著增强局部电场梯度，提升DEP作用力，将CNTs组装效率大幅提高（<90 s）；(2) 空间可编程组装——通过设计电极图案和电场参数，实现CNTs在特定位置、特定取向的精准沉积，构建任意角度的CNT阵列；(3) 高各向异性传感——制备的各向异性应变传感器在平行与垂直方向的灵敏度比高达16.52，循环稳定性>2000次；(4) 多维方向感知——通过构建直角传感器阵列，成功实现180°范围内应变大小与方向的同时检测。

　　2图文导读

　　图1、(a) Schematic of the sensor array, which could detect strain direction and magnitude simultaneously. (b) Schematic diagram of the fabrication processes of the sensor unit and sensor array.

　　图2.(a) Simulation model of the electric field distribution and direction of DEP force (black arrows). (b) Electric field distribution for the two electrode structures. (c) Electric field strength profiles for both electrode structures along a cross-sectional line 10 µm above the electrode surface. (d) Electric field strength variation curves at different heights along the upper surface of the electrodes for the two electrode structures (from 10 µm above the surface).

　　图3、(a) The distribution of electric field and DEP force (grey arrows) acting on a CNT with its major axis at different angles to the field. (b) The dynamic evolution of the angle between the major axis of the CNT and the direction of the electric field. (c) The distribution of the electric field and DEP force (grey arrows) acting on CNTs when they are respectively in parallel and end-to-end alignment states. (d) The dynamic evolution of the normalized separation distance (X/X0) between CNTs.

　　图4、(a) Equivalent circuit model of the CNT dispersion. (b) The curves of system impedance and its relative change as functions of CNT dispersion concentration after the application of the electric field, the maximum standard deviation is 152.66 kΩ and 4.88%, respectively. (c) The curves of system impedance and its relative change as functions of the applied electric field strength, the maximum standard deviation is 65.33 kΩ and 3.64%, respectively. (d) The curves of system impedance and its relative change as functions of the duration of the applied electric field, the maximum standard deviation is 64.07 kΩ and 2.79%, respectively.

　　图5、(a) Relative resistance changes versus strain for the sensors with different CNT dispersion concentration, the maximum standard deviation is 17.32%. (b) Relative resistance changes under 10% strain at different frequencies. (c) Relative resistance changes of the sensor unit induced by different repeated strains. (d) Resistance response of the sensor unit under stepwise strains from 5% to 20%, with each stage maintained for a certain duration. (e) The response time and relaxation time of the sensor unit. (f) Durability test of the sensor unit under 2000 stretching-releasing cycles at 5% strain.

　　图6、(a) The strain-relative resistance changes curves at different angles of the sensor unit. (b) Relative resistance response of the sensor unit under equal strain (ε = 5% and 10%) in different directions, exhibiting a nearly symmetrical distribution centered at 90°. (c) Pressure insensitivity test of the sensor unit at different pressure. (d) Schematic of the sensor array, consisting of three sensor units (Sensor 1, Sensor 2, and Sensor 3) arranged in a right-angle configuration, and the three arrows represent the three arrangement directions of CNT. (e–h) Relative resistance response of the sensor array under applied stretching angles of (e) 0°, (f) 45°, (g) 90°, and (h) 135°, exhibiting significant differences at various angles.

　　图7、Application demonstrations of the sensor unit and sensor array. The sensor unit records the different degrees of flexion movement of the (a) index finger or (b) wrist. The sensor array records the complex human motions, including (c) wrist motions and (d) shoulder motions.

　　3小结 

　　综上所述，本研究通过结构化电场调制，建立了一个用于制备各向异性碳纳米管/聚合物复合材料的可编程、电场引导型制造平台。借助锯齿状电极和优化的电场参数，实现了碳纳米管的高有序取向，从而制备出具有16.52灵敏度比且在2000个循环中仍保持优异耐久性的各向异性碳纳米管/聚二甲基硅氧烷（PDMS）复合材料。作为概念验证，基于该平台构建了一个直角传感器阵列，该阵列能够在完整的180°平面内明确识别应变幅值和方向，从而能够识别各种复杂的人体运动差异。除了这些具体的演示之外，结构化电场组装策略也易于应用于其他纳米材料和器件架构。因此，本研究为多向应变传感器的设计与制造提供了一条新途径，并在柔性电子学领域展现了应用潜力。

　　文献：