1. Ferroelectric-Like Non-Volatile FET With Amorphous Gate Insulator for Supervised Learning Applications
- Author
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Fenning Liu, Shulong Wang, Yan Liu, Wenwu Xiao, Xiao Yu, Yue Peng, Guosheng Wang, Genquan Han, Guoqing Zhang, and Yue Hao
- Subjects
Materials science ,Artificial neural network ,business.industry ,Transistor ,FET ,Long-term potentiation ,Dielectric ,oxygen vacancy ,Ferroelectricity ,Electronic, Optical and Magnetic Materials ,Amorphous solid ,law.invention ,STDP ,TK1-9971 ,law ,Electrode ,Amorphous ,LTD ,Optoelectronics ,Electrical engineering. Electronics. Nuclear engineering ,Electrical and Electronic Engineering ,LTP ,Polarization (electrochemistry) ,business ,Biotechnology - Abstract
We experimentally demonstrate ferroelectric-like non-volatile field-effect transistor (NVFET) with the amorphous Al2O3 gate insulator for artificial synapse applications. The switchable polarization (P) is attributed to the voltage modulation of mobile ions in the gate insulator. The ferroelectric-like NVFETs integrated with 3 nm and 6 nm-thick Al2O3 dielectrics demonstrate the capability to mimic various synaptic behaviors including long-term potentiation (LTP), long-term depression (LTD), and spike-timing-dependent plasticity (STDP), under different types of electrical stimuli to the gate electrode. To verify the application of the ferroelectric-like transistors in the Spike Neural Network (SNN), the online training has been carried out based on the synaptic characteristics of the devices, and a decent accuracy (>80%) is achieved for fixed-amplitude ±3 V/100 ns potentiation/depression pulses.
- Published
- 2021