Abstract
The gallop of artificial intelligence ignites urgent demand on information processing systems with ultralow power consumption, reliable multi-parameter control and high operation efficiency. Here, the poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)) wrapped InGaAs nanowire (NW) artificial synapses capable to operate with record-low subfemtojoule power consumption are presented. The essential synaptic behaviors are mimicked and modulated effectively by adjusting the thickness of top P(VDF-TrFE) films. Moreover, the long-term depression is realized by applying visible light (450 nm) because of the negative photoconductivity of InGaAs nanowires. Combined with optimal P(VDF-TrFE) films, the synaptic devices have the more linear long-term potentiation/depression characteristics and the faster supervised learning process simulated by hardware neural networks. The Pavlovian conditioning is also performed by combining electrical and infrared stimuli. Evidently, these ultralow-operating-power synapses are demonstrated with the brain-like behaviors, effective function modulation, and more importantly, the synergistic photoelectric modulation, which illustrates the promising potentials for neuromorphic computing systems.
| Original language | English |
|---|---|
| Article number | 106654 |
| Journal | Nano Energy |
| Volume | 91 |
| DOIs | |
| State | Published - Jan 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Artificial synapse
- Associative learning
- Ferroelectric polymer
- InGaAs nanowires
- Negative photoconductivity
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