Functional emulation of biological synapses using electronic devices is regarded as the first step toward neuromorphic engineering and artificial neural networks (ANNs). Electrolyte-gated transistors (EGTs) are mixed ionic–electronic conductivity devices capable of efficient gate-channel capacitance coupling, biocompatibility, and flexible architectures. Electrolyte gating offers significant advantages for the realization of neuromorphic devices/architectures, including ultralow-voltage operation and the ability to form parallel-interconnected networks with minimal hardwired connectivity. In this review, the most recent developments in EGT-based electronics are introduced with their synaptic behaviors and detailed mechanisms, including short-/long-term plasticity, global regulation phenomena, lateral coupling between device terminals, and spatiotemporal correlated functions. Analog memory phenomena allow for the implementation of perceptron-based ANNs. Due to their mixed-conductivity phenomena, neuromorphic circuits based on EGTs allow for facile interfacing with biological environments. We also discuss the future challenges in implementing low power, high speed, and reliable neuromorphic computing for large-scale ANNs with these neuromorphic devices. The advancement of neuromorphic devices that rely on EGTs highlights the importance of this field for neuromorphic computing and for novel healthcare technologies in the form of adaptable or trainable biointerfacing.
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March 2020
Review Article|
January 16 2020
Electrolyte-gated transistors for synaptic electronics, neuromorphic computing, and adaptable biointerfacing
Special Collection:
Brain Inspired Electronics
Haifeng Ling
;
Haifeng Ling
1
Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications
, Nanjing 210023, China
2
Department of Applied Physics, Hong Kong Polytechnic University
, Hong Kong, China
3
Department of Molecular Electronics, Max Planck Institute for Polymer Research
, Mainz 55128, Germany
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Dimitrios A. Koutsouras;
Dimitrios A. Koutsouras
3
Department of Molecular Electronics, Max Planck Institute for Polymer Research
, Mainz 55128, Germany
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Setareh Kazemzadeh
;
Setareh Kazemzadeh
4
Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology
, Eindhoven 5612AJ, The Netherlands
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Yoeri van de Burgt
;
Yoeri van de Burgt
4
Microsystems, Institute for Complex Molecular Systems, Eindhoven University of Technology
, Eindhoven 5612AJ, The Netherlands
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Feng Yan
;
Feng Yan
a)
2
Department of Applied Physics, Hong Kong Polytechnic University
, Hong Kong, China
a)Authors to whom correspondence should be addressed: apafyan@polyu.edu.hk and gkoupidenis@mpip-mainz.mpg.de
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Paschalis Gkoupidenis
Paschalis Gkoupidenis
a)
3
Department of Molecular Electronics, Max Planck Institute for Polymer Research
, Mainz 55128, Germany
a)Authors to whom correspondence should be addressed: apafyan@polyu.edu.hk and gkoupidenis@mpip-mainz.mpg.de
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a)Authors to whom correspondence should be addressed: apafyan@polyu.edu.hk and gkoupidenis@mpip-mainz.mpg.de
Note: This paper is part of the special collection on Brain Inspired Electronics.
Appl. Phys. Rev. 7, 011307 (2020)
Article history
Received:
July 30 2019
Accepted:
December 05 2019
Citation
Haifeng Ling, Dimitrios A. Koutsouras, Setareh Kazemzadeh, Yoeri van de Burgt, Feng Yan, Paschalis Gkoupidenis; Electrolyte-gated transistors for synaptic electronics, neuromorphic computing, and adaptable biointerfacing. Appl. Phys. Rev. 1 March 2020; 7 (1): 011307. https://doi.org/10.1063/1.5122249
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