High Sensitivity Optoelectronic Artificial Synapse Based on GaN Porous Nanocone Array for Neuromorphic Computing

Abstract Neuromorphic computing architecture, inspired by biological systems, is one of the key solutions to overcoming the von Neumann bottleneck. In particular, as a core component of artificial visual perception systems, optoelectronic synapses with high sensitivity and long memory retention hold significant potential applications. Herein, a two‐terminal GaN porous nanocone array (PNA) optoelectronic artificial synapse is designed and fabricated. The unique structure of the GaN PNA significantly enhances light absorption, achieving a responsivity of up to 2.07 × 10 ⁶ A W ⁻¹ and a specific detectivity ( D* ) of 3.50 × 10 ¹⁵ Jones. The persistent photoconductivity (PPC) effect, originated from surface states, exhibits a remarkably long decay characteristic time of up to 1204 s. This enables the synapses to emulate various key synaptic functions, including paired‐pulse facilitation (PPF), memory‐forgetting‐relearning processes, and the transition from short‐term potentiation (STP) to long‐term potentiation (LTP). Moreover, the GaN PNA optoelectronic artificial synapse demonstrates exceptional performance in artificial visual neural networks with a recognition accuracy approaching 93%. This work presents a novel solution for enhancing computational efficiency in artificial visual neural networks.