SiC@NiO Core-Shell Nanowire Networks-Based Optoelectronic Synapses for Neuromorphic Computing and Visual Systems at...

Area of Science:

• Materials Science
• Neuroscience
• Computer Engineering

Background:

• 1D nanowire networks offer brain-like structures for neuromorphic systems, potentially overcoming the von Neumann bottleneck.
• Neuromorphic synaptic devices aim for efficient sensing and computing with high processing rates and low power consumption.

Purpose of the Study:

• To develop high-temperature neuromorphic synaptic devices based on SiC@NiO core-shell nanowire networks.
• To investigate the optoelectronic memristor (NNOM) capabilities for synaptic plasticity and memory functions.

Main Methods:

• Fabrication of SiC@NiO core-shell nanowire networks for optoelectronic memristors (NNOMs).
• Experimental evaluation of synaptic plasticity (short/long-term, modulation) under electrical and optical stimuli.
• Testing of memory functions ('learning-forgetting-relearning') and Pavlovian conditioning principles.

Main Results:

• NNOMs demonstrated synaptic plasticity and memory functions under both electrical and optical stimulation at room temperature and up to 200 °C.
• A 5x3 optoelectronic synaptic array exhibited stable visual memory up to 200 °C.
• NNOMs replicated Pavlovian classical conditioning, showing visual heterologous synaptic functionality.

Conclusions:

• SiC@NiO nanowire-based NNOMs exhibit robust synaptic characteristics and high-temperature stability.
• These devices show potential for developing advanced artificial visual systems and refining neuromorphic computing architectures.