神经形态工程学
MNIST数据库
记忆电阻器
材料科学
计算机科学
突触重量
人工神经网络
传输(电信)
非易失性存储器
纳米技术
光电子学
电子工程
人工智能
电信
工程类
作者
Lingli Liu,Putu Andhita Dananjaya,Mun Yin Chee,Gerard Joseph Lim,Calvin Xiu Xian Lee,Wen Siang Lew
标识
DOI:10.1021/acsami.3c03974
摘要
Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it can concurrently execute signal transmission and memory operations. In this work, we present a complementary metal-oxide-semiconductor-compatible 3TM with highly linear weight update characteristics and a dynamic range of ∼15. The switching mechanism is governed by the migration of oxygen ions and protons in and out of the channel under an external gate electric field. The involvement of the protonic defects in the electrochemical reactions is proposed based on the bipolar pulse trains required to initiate the oxidation process and the device electrical characteristics under different humidity levels. For the synaptic operation, an excellent endurance performance with over 256k synaptic weight updates was demonstrated while maintaining a stable dynamic range. Additionally, the synaptic performance of the 3TM is simulated and implemented into a four-layer neural network (NN) model, achieving an accuracy of ∼92% in MNIST handwritten digit recognition. With such desirable conductance modulation characteristics, our proposed 3T-memristor is a promising synaptic device candidate to realize the hardware implementation of the artificial NN.
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