He Yongli, Zhu Yixin, Wan Qing
Yongjiang Laboratory (Y-LAB), Ningbo 315202, China.
National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.
Nanomaterials (Basel). 2024 Mar 27;14(7):584. doi: 10.3390/nano14070584.
Current computing systems rely on Boolean logic and von Neumann architecture, where computing cells are based on high-speed electron-conducting complementary metal-oxide-semiconductor (CMOS) transistors. In contrast, ions play an essential role in biological neural computing. Compared with CMOS units, the synapse/neuron computing speed is much lower, but the human brain performs much better in many tasks such as pattern recognition and decision-making. Recently, ionic dynamics in oxide electrolyte-gated transistors have attracted increasing attention in the field of neuromorphic computing, which is more similar to the computing modality in the biological brain. In this review article, we start with the introduction of some ionic processes in biological brain computing. Then, electrolyte-gated ionic transistors, especially oxide ionic transistors, are briefly introduced. Later, we review the state-of-the-art progress in oxide electrolyte-gated transistors for ionic neuromorphic computing including dynamic synaptic plasticity emulation, spatiotemporal information processing, and artificial sensory neuron function implementation. Finally, we will address the current challenges and offer recommendations along with potential research directions.
当前的计算系统依赖于布尔逻辑和冯·诺依曼架构,其中计算单元基于高速电子传导互补金属氧化物半导体(CMOS)晶体管。相比之下,离子在生物神经计算中起着至关重要的作用。与CMOS单元相比,突触/神经元的计算速度要低得多,但人类大脑在模式识别和决策等许多任务中表现得更好。最近,氧化物电解质门控晶体管中的离子动力学在神经形态计算领域引起了越来越多的关注,这与生物大脑中的计算方式更为相似。在这篇综述文章中,我们首先介绍生物大脑计算中的一些离子过程。然后,简要介绍电解质门控离子晶体管,特别是氧化物离子晶体管。随后,我们回顾了用于离子神经形态计算的氧化物电解质门控晶体管的最新进展,包括动态突触可塑性模拟、时空信息处理以及人工感觉神经元功能实现。最后,我们将阐述当前面临的挑战,并提出建议以及潜在的研究方向。