Cavity‐Enhanced High Sensitivity InP Nanosheet Optoelectronic Synaptic Transistors for Neuromorphic Computing

ABSTRACT Optoelectronic synaptic transistors that combine sensing and computing functionalities are emerging as key components for next‐generation neuromorphic systems, yet their scalability and performance remain limited by device architecture and fabrication constraints. Here, we report cavity‐enhanced optoelectronic synaptic transistors based on surface‐state modulation in selectively grown InP nanosheets. Benefiting from optical‐cavity‐induced high gain and effective dark‐current suppression, the device exhibits an ultrahigh responsivity of approximately 1.5 × 10 6 A W −1 , a specific detectivity of ≈5 × 10 14 Jones, and a noise‐equivalent power of ≈10 −16 W Hz −1/2 . Precise control of charge dynamics at surface states using electrical and optical stimuli allows the emulation of key synaptic functions, including short‐ and long‐term plasticity, paired‐pulse facilitation, and learning–forgetting–relearning behaviors. Furthermore, convolutional neural network simulations leveraging the device's continuously tunable conductance yield image recognition accuracies approaching 90%. These results establish InP nanosheet optoelectronic synaptic transistors as a scalable and high‐performance platform for integrated neuromorphic computing.