A Lithium‐Ion‐Driven Electrolyte‐Gated 2D Synaptic Transistor Based on Se _0.3 Te _0.7 Nanosheet for Reservoir Computing

Abstract The solid‐state electrolyte has been explored as a gate dielectric for neuromorphic computing, offering enhanced gate controllability and enabling synaptic behaviors. However, the integration of solid‐state electrolytes with 2D materials to develop high‐performance reservoir computing (RC) systems remains rarely explored. In this study, an electrolyte‐gated synaptic transistor (EGST) integrated with 2D Se _0.3 Te _0.7 nanosheet and lithium phosphorus oxynitride (LiPON) solid‐state electrolyte is proposed. This device leverages ion‐carrier coupling to effectively modulate channel conductance (achieving an on/off current ratio of ≈7 × 10 ³ ) and exhibits a range of synaptic plasticity, including excitatory/inhibitory postsynaptic currents (EPSC/IPSC) and paired‐pulse facilitation (PPF), which are driven by the intrinsic nonlinearity of ionic dynamics. Building on these capabilities, a 2D‐EGST‐based RC system is simulated and demonstrate its computational capability through a handwritten digit classification task using the Modified National Institute of Standards and Technology (MNIST) dataset. The system achieves an identification accuracy exceeding 90%, outperforming the previously reported performance of other electrolyte‐gated transistor (EGT)‐based RC systems. It is believed that the 2D‐EGST offers new insights into the interplay between electronics and ion dynamics in 2D materials combined with solid‐state electrolytes, thereby paving the way for future applications of 2D‐EGST in neuromorphic computing.