Self-Assembly of 3D-Printed Multiscale Micropillar-Based Organic Electrochemical Transistors for Ultrasensitive Dopamine Sensing
Xinzhao Zhou, Liwen Zhang, Shengbin Zhang, Jing Liang, Ke Zhang, Zehui Zhao, Song Zhao, Y. Wang, Yurun Guo, Deyuan Zhang, Lei Jiang, Huawei Chen
Abstract
Organic electrochemical transistors (OECTs) with self-amplification have emerged as a promising approach for dopamine monitoring. However, the planar gate electrode structures in current OECTs significantly hinder the improvement of sensitive dopamine detection. Here, we develop an aerosol jet three-dimensional (3D) printing method to generate multiscale micropillar-based OECTs with tunable nanofeatures for ultrasensitive DA detection. Temperature-induced self-assembly nanoclusters are explored to replace atomized microdroplets to generate multiscale micropillars, and their diameter-tuning mechanism is clarified to enable on-demand nanofeature control. We fabricate micropillar electrodes with varying surface morphologies, array numbers, and heights, and uncover their micronano synergic enhancement effects on the mass transfer, catalytic efficiency, and ion migration that determine the sensing performance of the OECT. When the nanocluster diameter is 540 nm, the OECT achieves a maximized sensitivity of 254 mV/decade and an ultralow dopamine detection limit of 0.6 fM, which is 6 orders of magnitude lower than current methods. Integrated with a flexible circuit, the device allows real-time, wireless, and highly sensitive dopamine sensing in the rabbit brain, demonstrating its potential for future applications in the precise diagnosis and treatment of mental illnesses.