Research progress in gallium nitride-based artificial synaptic devices

Artificial synaptic devices that can emulate the functions of biological synapses and offer the advantages of brain-like computation are garnering considerable interest, as they have the potential to innovatively circumvent the von Neumann bottleneck at the device level. The foundation of research in artificial synaptic devices is the development of functional materials facilitating multilevel conductance state switching and storage. Gallium nitride (GaN), a third-generation semiconductor material with exceptional properties, has been used to implement artificial synaptic devices for neuromorphic computing. GaN-based artificial synapses have been demonstrated to enable a wide range of neuromorphic characteristics, exhibiting high photovoltaic efficiency, stability, low power consumption, and UV responsiveness. The intrinsic properties of GaN itself and in combination with other materials offer many possibilities for emulating synaptic function, which gives GaN materials the prospect of becoming the cornerstone of neuromorphic computing systems. Herein, to more fully comprehend the potential of GaN-based artificial synaptic devices in future neuromorphic systems, this paper reviews recent advancements in GaN synthesis and GaN-based artificial synapses driven by different working mechanisms. It also analyzes the prospective applications of GaN-based artificial synapses and the challenges likely to be encountered in their subsequent evolution. This review may be a significant turning point for developing neuromorphic computing using GaN materials.