Hybrid Optical-Electrical Pulst Programming in FeFETs for High-Precision Neuromorphic Computing

초록

Advances in artificial intelligence (AI) are accelerating new paradigms in neuromorphic computing that enable real-time, low-power signal processing through brain-inspired architectures. In particular, hardware neural networks capable of emulating synaptic behavior are drawing attention for their potential in highly efficient, parallel computation. To realize such functionality, we developed a nonvolatile synaptic memory device based on a ferroelectric field-effect transistor (FeFET), employing a transition metal dichalcogenide (TMDC) channel and a P(VDF?TrFE) ferroelectric gate insulator. The device exhibits stable synaptic weight modulation and long-term retention, highlighting its promise for next-generation neuromorphic processors and in-memory computing platforms.