| Literature DB >> 31025562 |
Qingzhou Liu, Yihang Liu, Ji Li, Christian Lau, Fanqi Wu, Anyi Zhang, Zhen Li, Mingrui Chen, Hongyu Fu, Jeffrey Draper, Xuan Cao, Chongwu Zhou.
Abstract
Nonvolatile, flexible artificial synapses that can be used for brain-inspired computing are highly desirable for emerging applications such as human-machine interfaces, soft robotics, medical implants, and biological studies. Printed devices based on organic materials are very promising for these applications due to their sensitivity to ion injection, intrinsic printability, biocompatibility, and great potential for flexible/stretchable electronics. Herein, we report the experimental realization of a nonvolatile artificial synapse using organic polymers in a scalable fabrication process. The three-terminal electrochemical neuromorphic device successfully emulates the key features of biological synapses: long-term potentiation/depression, spike timing-dependent plasticity learning rule, paired-pulse facilitation, and ultralow energy consumption. The artificial synapse network exhibits an excellent endurance against bending tests and enables a direct emulation of logic gates, which shows the feasibility of using them in futuristic hierarchical neural networks. Based on our demonstration of 100 distinct, nonvolatile conductance states, we achieved a high accuracy in pattern recognition and face classification neural network simulations.Entities:
Keywords: artificial synapses; flexible electronics; neuromorphic computing; organic electronics; printed electronics
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Year: 2019 PMID: 31025562 DOI: 10.1021/acsami.9b00226
Source DB: PubMed Journal: ACS Appl Mater Interfaces ISSN: 1944-8244 Impact factor: 9.229