铁电性
材料科学
神经形态工程学
光电子学
相变存储器
晶体管
纳米技术
计算机科学
电压
电气工程
人工神经网络
机器学习
电介质
工程类
图层(电子)
作者
Chunlai Luo,Yan Zhang,Wentao Shuai,Kexin He,Ming Li,Ruiqiang Tao,Deyang Chen,Zhen Fan,Bin Zhang,Xiaoyuan Zhou,Jiyan Dai,Guofu Zhou,Xubing Lu,Jun‐Ming Liu
标识
DOI:10.1007/s40843-022-2359-6
摘要
Benefiting from the nonvolatile and fast programming operations of ferroelectric materials, ferroelectric synaptic transistors (FSTs) are promising in neuromorphic computing. However, it is challenging to realize conductance with a large dynamic range (Gmax/Gmin) and multilevel states simultaneously under low energy consumption. Here, solution-processed indium oxide (In2O3) synaptic transistors gated by ferroelectric Hf0.5Zr0.5O2 (HZO) are proposed for the first time to address the above problems. Excellent synaptic characteristics were realized through the delicately regulated ferroelectric phase and good inhibition of charge injection in ferroelectric bulk and ferroelectric/semiconductor interface. Long-term potentiation/depression (LTP/D) up to 101 effective conductance states and excellent endurance (>1000 cycles) with large Gmax/Gmin = 32.2 were successfully mimicked under a low energy consumption of 490 fJ per spike event. Besides, the simulation achieved 96.5% recognition accuracy of handwriting digit, which is the highest record for existing FSTs. This work provides a new pathway for developing low-cost, high-performance, and energy-efficient FSTs.
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