An extremely low-power-consumption reconfigurable two-dimensional tellurene artificial synapse for bio-inspired wearable edge computing
- Authors
- You, Bolim; Yoon, Jeechan; Kim, Yuna; Yang, Mino; Bak, Jina; Park, Jihyang; Kim, Un Jeong; Hahm, Myung Gwan; Lee, Moonsang
- Issue Date
- May-2024
- Publisher
- Royal Society of Chemistry
- Keywords
- Biomimetics; Electric Power Utilization; Flexible Electronics; Wearable Technology; Artificial Synapse; Bio-implantable; Computing System; Edge Computing; Implantable Electronics; Low-power Consumption; Lower-power Consumption; Neuromorphic; Reconfigurable; Two-dimensional
- Citation
- Journal of Materials Chemistry C, v.12, no.18, pp 6596 - 6605
- Pages
- 10
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Materials Chemistry C
- Volume
- 12
- Number
- 18
- Start Page
- 6596
- End Page
- 6605
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/26061
- DOI
- 10.1039/d4tc00530a
- ISSN
- 2050-7526
2050-7534
- Abstract
- Neuromorphic electronics are gaining significant interest as components of next-generation computing systems. However, it is difficult to develop flexible neuromorphic electronics for implementation in various edge applications such as bio-implantable electronics and neuroprosthetics. In this study, we present a reconfigurable 2D tellurene (Te) artificial synaptic transistor on a flexible substrate for neuromorphic edge computing. Single-crystalline 2D Te flexible synaptic transistors exhibit potentiation and depression modulated by gate pulses with an extremely low power consumption of 9 fJ, 93 effective multilevel states, excellent linearity and symmetry, and an accuracy of 93% in recognizing the Modified National Institute of Standards and Technology (MNIST) patterns. Furthermore, it was observed to be a flexible synaptic transistor with outstanding gate tunability and endurance characteristics, even under a 2% curvature in both the concave and convex states. We believe a robust 2D Te flexible artificial synapse will effectively function as a building block for wearable neuromorphic edge computing applications. We fabricated a reconfigurable two-dimensional tellurene artificial synaptic transistor on a flexible substrate for bio-inspired wearable neuromorphic edge computing, showing an extremely low power consumption of 9 fJ and an impressive accuracy of 93% in recognizing MNIST patterns.
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Collections - College of Natural Science > Department of Physics > 1. Journal Articles

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