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Designing High‐Performance Storage in HfO<sub>2</sub>/BiFeO<sub>3</sub> Memristor for Artificial Synapse Applications

Lei Liu, Wen Xiong, Yanxin Liu, Kaige Chen, Zhong Xu, Yi Zhou, Han Jia, Cong Ye, Xin Chen, Zhitang Song, Min Zhu

2020Advanced Electronic Materials101 citationsDOI

Abstract

Abstract HfO 2 ‐based memristors that remembers the history of the current that has passed through them have attracted great interest for use as artificial synapses in neuromorphic systems. However, the low resistance contrast exhibited by HfO 2 ‐based memristors seriously decreases their recognition accuracy. By inserting a 2 nm BiFeO 3 layer a large memory window of 10 4 and remarkable pulse endurance of 10 8 cycles are achieved. Multilevel storage capability is also demonstrated by controlling the stop voltages in the RESET process. The conductance–modulation characteristics of a BiFeO 3 /HfO 2 memristor can be used to mimic the learning behaviors of biological synapses, and spiking timing dependent plasticity is mimicked, which is viewed as an important learning rule of biological synapses. Moreover pattern learning and memorization ability like the human brain are achieved by a 3 × 3 memristive device array.

Topics & Concepts

Neuromorphic engineeringMemristorMaterials scienceMemorizationReset (finance)SynapseVoltageOptoelectronicsProcess (computing)NanotechnologyComputer scienceElectronic engineeringArtificial intelligenceArtificial neural networkNeuroscienceElectrical engineeringEngineeringBiologyMathematics educationMathematicsEconomicsFinancial economicsOperating systemAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeuroscience and Neural Engineering
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