Electrolyte-gated optoelectronic transistors for neuromorphic applications

Abstract The traditional von Neumann architecture has demonstrated inefficiencies in parallel computing and adaptive learning, rendering it incapable of meeting the growing demand for efficient and high-speed computing. Neuromorphic computing with significant advantages such as high parallelism and ultra-low power consumption is regarded as a promising pathway to overcome the limitations of conventional computers and achieve the next-generation artificial intelligence. Among various neuromorphic devices, the artificial synapses based on electrolyte-gated transistors stand out due to their low energy consumption, multimodal sensing/recording capabilities, and multifunctional integration. Moreover, the emerging optoelectronic neuromorphic devices which combine the strengths of photonics and electronics have demonstrated substantial potential in the neuromorphic computing field. Therefore, this article reviews recent advancements in electrolyte-gated optoelectronic neuromorphic transistors. First, it provides an overview of artificial optoelectronic synapses and neurons, discussing aspects such as device structures, operating mechanisms, and neuromorphic functionalities. Next, the potential applications of optoelectronic synapses in different areas such as artificial visual system, pain system, and tactile perception systems are elaborated. Finally, the current challenges are summarized, and future directions for their developments are proposed.