Biological receptor-inspired flexible artificial synapse based on ionic dynamics

Qifeng Lu, Fuqin Sun, Lin Liu, Lianhui Li, Yingyi Wang, Mingming Hao, Zihao Wang, Shuqi Wang, Ting Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

The memristor has been regarded as a promising candidate for constructing a neuromorphic computing platform that is capable of confronting the bottleneck of the traditional von Neumann architecture. Here, inspired by the working mechanism of the G-protein-linked receptor of biological cells, a novel double-layer memristive device with reduced graphene oxide (rGO) nanosheets covered by chitosan (an ionic conductive polymer) as the channel material is constructed. The protons in chitosan and the functional groups in rGO nanosheets imitate the functions of the ligands and receptors of biological cells, respectively. Smooth changes in the response current depending on the historical applied voltages are observed, offering a promising pathway toward biorealistic synaptic emulation. The memristive behavior is mainly a result of the interaction between protons provided by chitosan and the defects and functional groups in the rGO nanosheets. The channel current is due to the hopping of protons through functional groups and is limited by the traps in the rGO nanosheets. The transition from short-term to long-term potentiation is achieved, and learning-forgetting behaviors of the memristor mimicking those of the human brain are demonstrated. Overall, the bioinspired memristor-type artificial synaptic device shows great potential in neuromorphic networks.

Original languageEnglish
Article number84
JournalMicrosystems and Nanoengineering
Volume6
Issue number1
DOIs
Publication statusPublished - 1 Dec 2020
Externally publishedYes

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