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- Title
Photonic Organolead Halide Perovskite Artificial Synapse Capable of Accelerated Learning at Low Power Inspired by Dopamine‐Facilitated Synaptic Activity.
- Authors
Ham, Seonggil; Choi, Sanghyeon; Cho, Haein; Na, Seok‐In; Wang, Gunuk
- Abstract
The ability of high‐order tuning of the synaptic plasticity in an artificial synapse can offer significant improvement in the processing time, low‐power recognition, and learning capability in a neuro‐inspired computing system. Inspired by light‐assisted dopamine‐facilitated synaptic activity, which achieves rapid learning and adaptation by lowering the threshold of the synaptic plasticity, a two‐terminal organolead halide perovskite (OHP)‐based photonic synapse is fabricated and designed in which the synaptic plasticity is modified by both electrical pulses and light illumination. Owing to the accelerated migration of the iodine vacancy inherently existing in the coated OHP film under light illumination, the OHP synaptic device exhibits light‐tunable synaptic functionalities with very low programming inputs (≈0.1 V). It is also demonstrated that the threshold of the long‐term potentiation decreases and synaptic weight further modulates when light illuminates the device, which is phenomenologically analogous to the dopamine‐assisted synaptic process. Notably, under light exposure, the OHP synaptic device achieves rapid pattern recognition with ≈81.8% accuracy after only 2000 learning phases (60 000 learning phases = one epoch) with a low‐power consumption (4.82 nW/the initial update for potentiation), which is ≈2.6 × 103 times lower than when the synaptic weights are updated by only high electrical pulses. A two‐terminal organolead halide perovskite (OHP)‐based photonic synapse exhibits a reliable bipolar switching behavior and replicates the essential synaptic functionalities such as STP, LTP, and LTD controlled by both electrical and light stimuli. This enables high‐order tuning of the synaptic plasticity, which can accelerate the learning capability with a lower power in a neuro‐inspired hardware architecture.
- Subjects
PEROVSKITE; HALIDES; DOPAMINE; NEUROPLASTICITY; ARTIFICIAL neural networks
- Publication
Advanced Functional Materials, 2019, Vol 29, Issue 5, pN.PAG
- ISSN
1616-301X
- Publication type
Article
- DOI
10.1002/adfm.201806646