4.8 Review

Evolution of Bio-Inspired Artificial Synapses: Materials, Structures, and Mechanisms

Journal

SMALL
Volume 17, Issue 9, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/smll.202000041

Keywords

artificial synapses; energy consumption; memristors; synaptic plasticity; synaptic transistors

Funding

  1. Tianjin Science Foundation for Distinguished Young Scholars [19JCJQJC61000]
  2. Key Area R&D Project of Guangdong Province [2018B030338001]
  3. Hundred Young Academic Leaders Program of Nankai University [2122018218]
  4. Natural Science Foundation of Tianjin [18JCYBJC16000]
  5. National Natural Science Foundation of China (NSFC) [51573036]
  6. 111 Project [B16027]
  7. International Cooperation Base [2016D01025]
  8. Tianjin International Joint Research and Development Center
  9. Graduate Research and Innovation Project of Tianjin [2019YJSS089]

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Artificial synapses (ASs) are electronic devices that mimic important functions of biological synapses in artificial neuromorphic networks for brain-inspired computing. They need to simulate a range of biological synaptic functions and minimize feature size and energy consumption for high-density energy-efficient integration.
Artificial synapses (ASs) are electronic devices emulating important functions of biological synapses, which are essential building blocks of artificial neuromorphic networks for brain-inspired computing. A human brain consists of several quadrillion synapses for information storage and processing, and massively parallel computation. Neuromorphic systems require ASs to mimic biological synaptic functions, such as paired-pulse facilitation, short-term potentiation, long-term potentiation, spatiotemporally-correlated signal processing, and spike-timing-dependent plasticity, etc. Feature size and energy consumption of ASs need to be minimized for high-density energy-efficient integration. This work reviews recent progress on ASs. First, synaptic plasticity and functional emulation are introduced, and then synaptic electronic devices for neuromorphic computing systems are discussed. Recent advances in flexible artificial synapses for artificial sensory nerves are also briefly introduced. Finally, challenges and opportunities in the field are discussed.

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