Flexible electronic synapse enabled by ferroelectric field effect transistor for robust neuromorphic computing

Zhong, Gaokuo1; Zi, Mengfei1,2; Ren, Chuanlai1,2; Xiao, Qun1,2; Tang, Mingkai1,2; Wei, Liyu1; An, Feng1,2; Xie, Shuhong2; Wang, Jinbin2; Zhong, Xiangli2; Huang, Mingqiang1; Li, Jiangyu1,3

2020-08-31

10.1063/5.0013638

APPLIED PHYSICS LETTERS   影响因子和分区

0003-6951

1077-3118

Neuromorphic computing has the potential to accelerate high performance parallel and low power in-memory computation, artificial intelligence, and adaptive learning. Despite emulating the basic functions of biological synapses well, the existing artificial electronic synaptic devices have yet to match the softness, robustness, and ultralow power consumption of the brain. Here, we demonstrate an all-inorganic flexible artificial synapse enabled by a ferroelectric field effect transistor based on mica. The device not only exhibits excellent electrical pulse modulated conductance updating for synaptic functions but also shows remarkable mechanical flexibility and high temperature reliability, making robust neuromorphic computation possible under external disturbances such as stress and heating. Based on its linear, repeatable, and stable long-term plasticity, we simulate an artificial neural network for the Modified National Institute of Standards and Technology handwritten digit recognition with an accuracy of 94.4%. This work provides a promising way to enable flexible, low-power, robust, and highly efficient neuromorphic computation that mimics the brain.

SCI ; EI

英语

NI期刊

通讯

National Natural Science Foundation of China[51902337] ; Shenzhen Science and Technology Innovation Committee[KQTD20170810160424889][JCYJ20170818163902553][JCYJ20170818155813437] ; Key-Area Research and Development Program of Guangdong Province[2018B010109009] ; Guangdong Science and Technology Innovation Committee[2019A1515111142]

Physics

Physics, Applied

WOS:000568858800001

AMER INST PHYSICS

20203809188295

Mica ; Ferroelectricity ; Field effect transistors ; Neural networks ; Computing power

Minerals:482.2 ; Electricity: Basic Concepts and Phenomena:701.1 ; Semiconductor Devices and Integrated Circuits:714.2 ; Computer Peripheral Equipment:722.2 ; Digital Computers and Systems:722.4 ; Computer Software, Data Handling and Applications:723

PHYSICS

Web of Science

1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen Key Lab Nanobiomech, Shenzhen 518055, Peoples R China
2.Xiangtan Univ, Sch Mat Sci & Engn, Xiangtan 411105, Peoples R China
3.Southern Univ Sci & Technol, Dept Mat Sci & Engn, Shenzhen 518055, Guangdong, Peoples R China

Zhong, Gaokuo,Zi, Mengfei,Ren, Chuanlai,et al. Flexible electronic synapse enabled by ferroelectric field effect transistor for robust neuromorphic computing[J]. APPLIED PHYSICS LETTERS,2020,117(9).

Zhong, Gaokuo.,Zi, Mengfei.,Ren, Chuanlai.,Xiao, Qun.,Tang, Mingkai.,...&Li, Jiangyu.(2020).Flexible electronic synapse enabled by ferroelectric field effect transistor for robust neuromorphic computing.APPLIED PHYSICS LETTERS,117(9).

Zhong, Gaokuo,et al."Flexible electronic synapse enabled by ferroelectric field effect transistor for robust neuromorphic computing".APPLIED PHYSICS LETTERS 117.9(2020).