The Rise of Organic Electrochemical Transistors for Brain-Inspired Neuromorphic Computing

Abstract

As modern data-driven technologies represented by artificial intelligence (AI) systems increasingly demand energy-efficient, real-time data processing, a new computing paradigm that transcends the energy and speed limits of conventional von Neumann architectures has been proposed to emulate brain-inspired information processing. Neuromorphic computing offers a brain-inspired alternative that integrates memory and computation within the same device platform enabling energy-efficient, parallel computing operation. Among emerging device platforms, organic electrochemical transistors (OECTs) have attracted particular attention due to their distinct advantages such as mixed ionic-electronic conduction, high transconductance, low-voltage operation, and intrinsic biocompatibility. These features make OECTs potentially suited for artificial synaptic and neuronal devices capable of mimicking characteristic plastic and spiking behaviors of biological nerve. Herein, we provide a comprehensive overview of OECT-based neuromorphic electronics, covering from fundamental device physics, fabrication techniques, materials, and architectural advances to their realization as artificial synapse and nerve. Furthermore, recent progress in higher-level integration of those elements and advanced OECT platforms such as reconfigurable and multimodal devices which combine electrical, optical, and biochemical functionalities has been discussed. Finally, we outline the remaining challenges and future directions for achieving stable, practical OECT neuromorphic hardware toward next-generation intelligent, low-power, and biohybrid computing.