Tailoring Classical Conditioning Behavior in TiO₂ Nanowires: ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware.

ABSTRACT: Neuromorphic hardware equipped with associative learning capabilities presents fascinating applications in the next generation of artificial intelligence. However, research into synaptic devices exhibiting complex associative learning behaviors is still nascent. Here, an optoelectronic memristor based on Ag/TiO₂ Nanowires: ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors. Effective implementation of synaptic behaviors, including long and short-term plasticity, and learning-forgetting-relearning behaviors, were achieved in the device through the application of light and electrical stimuli. Leveraging the optoelectronic co-modulated characteristics, a simulation of neuromorphic computing was conducted, resulting in a handwr

SUBMITTER: Wang W 

PROVIDER: S-EPMC10899558 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature