神经形态工程学
材料科学
铁电性
神经促进
光电子学
突触重量
长时程增强
晶体管
计算机科学
人工神经网络
电压
电气工程
人工智能
电介质
生物化学
工程类
受体
化学
作者
Duho Kim,Yu‐Rim Jeon,Bon‐Cheol Ku,Chulwon Chung,Tae Heun Kim,Sang‐Hyeok Yang,Uiyeon Won,Tae-Ho Jeong,Changhwan Choi
标识
DOI:10.1021/acsami.1c12735
摘要
Neuromorphic computing has garnered significant attention because it can overcome the limitations of the current von-Neumann computing system. Analog synaptic devices are essential for realizing hardware-based artificial neuromorphic devices; however, only a few systematic studies in terms of both synaptic materials and device structures have been conducted so far, and thus, further research is required in this direction. In this study, we demonstrate the synaptic characteristics of a ferroelectric material-based thin-film transistor (FeTFT) that uses partial switching of ferroelectric polarization to implement analog conductance modulation. For a ferroelectric material, an aluminum-doped hafnium oxide (Al-doped HfO2) thin film was prepared by atomic layer deposition. As an analog synaptic device, our FeTFT successfully emulated short-term plasticity and long-term plasticity characteristics, such as paired-pulse facilitation and spike timing-dependent plasticity. In addition, we obtained potentiation/depression weight updates with high linearity, an on/off ratio, and low cycle-to-cycle variation by adjusting the amplitude and number of input pulses. In the simulation trained with optimized potentiation/depression conditions, we achieved a pattern recognition accuracy of approximately 90% for the Modified National Institute of Standard and Technology (MNIST) handwritten data set. Our results indicated that ferroelectric transistors can be used as an alternative artificial synapse.
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