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有机人工神经:神经形态机器人技术与生物电子学

Organic Artificial Nerves: Neuromorphic Robotics and Bioelectronics.

作者信息

Sung Min-Jun, Kim Kwan-Nyeong, Kim Chunghee, Lee Hyun-Haeng, Lee Seung-Woo, Kim Somin, Seo Dae-Gyo, Zhou Huanyu, Lee Tae-Woo

机构信息

Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea.

BK21 PLUS SNU Materials Division for Educating Creative Global Leaders, Seoul National University, Seoul 08826, Republic of Korea.

出版信息

Chem Rev. 2025 Mar 12;125(5):2625-2664. doi: 10.1021/acs.chemrev.4c00571. Epub 2025 Feb 21.

Abstract

Neuromorphic electronics are inspired by the human brain's compact, energy-efficient nature and its parallel-processing capabilities. Beyond the brain, the entire human nervous system, with its hierarchical structure, efficiently preprocesses complex sensory information to support high-level neural functions such as perception and memory. Emulating these biological processes, artificial nerve electronics have been developed to replicate the energy-efficient preprocessing observed in human nerves. These systems integrate sensors, artificial neurons, artificial synapses, and actuators to mimic sensory and motor functions, surpassing conventional circuits in sensor-integrated electronics. Organic synaptic transistors (OSTs) are key components in constructing artificial nerves, offering tunable synaptic plasticity for complex sensory processing and the mechanical flexibility required for applications in soft robotics and bioelectronics. Compared to traditional sensor-integrated electronics, early implementations of organic artificial nerves (OANs) incorporating OSTs have demonstrated a higher signal-to-noise ratio, lower power consumption, and simpler circuit designs along with on-device processing capabilities and precise control of actuators and biological limbs, driving progress in neuromorphic robotics and bioelectronics. This paper reviews the materials, device engineering, and system integration of the OAN design, highlights recent advancements in neuromorphic robotics and bioelectronics utilizing the OANs, and discusses current challenges and future research directions.

摘要

神经形态电子学的灵感来源于人类大脑紧凑、节能的特性及其并行处理能力。除了大脑之外,具有层次结构的整个人类神经系统能够有效地对复杂的感官信息进行预处理,以支持诸如感知和记忆等高级神经功能。为了模拟这些生物过程,人们开发了人工神经电子学来复制在人类神经中观察到的节能预处理。这些系统集成了传感器、人工神经元、人工突触和执行器,以模仿感官和运动功能,在集成传感器的电子学方面超越了传统电路。有机突触晶体管(OST)是构建人工神经的关键组件,为复杂的感官处理提供了可调谐的突触可塑性,以及在软机器人和生物电子学应用中所需的机械灵活性。与传统的集成传感器电子学相比,早期采用OST的有机人工神经(OAN)实现已经展示出更高的信噪比、更低的功耗、更简单的电路设计以及片上处理能力和对执行器及生物肢体的精确控制,推动了神经形态机器人和生物电子学的发展。本文综述了OAN设计的材料、器件工程和系统集成,重点介绍了利用OAN在神经形态机器人和生物电子学方面的最新进展,并讨论了当前的挑战和未来的研究方向。

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