Cientistas criam sinapses artificiais: mais uma etapa em direção a um computador que "funcione" como o cérebro humano

terça-feira, julho 05, 2016

Organic core-sheath nanowire artificial synapses with femtojoule energy consumption

Wentao Xu1, Sung-Yong Min1, Hyunsang Hwang1 and Tae-Woo Lee1,2,*

- Author Affiliations

1Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang 790-784, Republic of Korea.

2Department of Chemical Engineering, Division of Advanced Materials Science, School of Environmental Science and Engineering, POSTECH, 77 Cheongam-Ro, Nam-Gu, Pohang 790-784, Republic of Korea.

↵*Corresponding author. Email: twlee@postech.ac.kr; taewlees@gmail.com

Science Advances 17 Jun 2016:

Vol. 2, no. 6, e1501326


Fig. 1
Schematic of biological neuronal network and an ONW ST that emulates a biological synapse.

Abstract

Emulation of biological synapses is an important step toward construction of large-scale brain-inspired electronics. Despite remarkable progress in emulating synaptic functions, current synaptic devices still consume energy that is orders of magnitude greater than do biological synapses (~10 fJ per synaptic event). Reduction of energy consumption of artificial synapses remains a difficult challenge. We report organic nanowire (ONW) synaptic transistors (STs) that emulate the important working principles of a biological synapse. The ONWs emulate the morphology of nerve fibers. With a core-sheath–structured ONW active channel and a well-confined 300-nm channel length obtained using ONW lithography, ~1.23 fJ per synaptic event for individual ONW was attained, which rivals that of biological synapses. The ONW STs provide a significant step toward realizing low-energy–consuming artificial intelligent electronics and open new approaches to assembling soft neuromorphic systems with nanometer feature size.

Keywords artificial synapse organic nanowire energy consumption organic electronics bio-inspired electronics short-term plasticity long-term plasticity
Copyright © 2016, The Authors

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