Abstract
Recently, hardware implementation of neuromorphic device in the optical domain is considered as one of the most promising routes to realize energy-efficient neuromorphic computing systems. Especially, a complete plasticity modulation by all-photonic stimulation has been one of the most important challenges for implementation of an optoelectronic neuromorphic device. Here, we demonstrate a fully optically driven bidirectional synaptic device using ionic electrolyte transistors. The photovoltaic divider enables wavelength-selective light-to-voltage conversion and subsequently induces ionic migration in the electrolyte, resulting in the synaptic potentiation or depression. Based on the synaptic characteristics, pattern recognition with an accuracy up to 90.1% is obtained in the Modified National Institute of Standards and Technology simulation.
Original language | English |
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Pages (from-to) | 2629-2635 |
Number of pages | 7 |
Journal | ACS Applied Electronic Materials |
Volume | 4 |
Issue number | 6 |
DOIs | |
State | Published - 28 Jun 2022 |
Keywords
- ionic electrolyte transistor
- metal chalcogenide
- neuromorphic computing
- optically driven synaptic device
- pattern recognition