Research on electronic synaptic simulation of HfO2-based memristor by embedding Al2O3

Jinfu Lin; Hongxia Liu; Shulong Wang

doi:10.1088/1361-6528/acfd31

Research on electronic synaptic simulation of HfO₂-based memristor by embedding Al₂O₃

Nanotechnology. 2023 Oct 13;35(1). doi: 10.1088/1361-6528/acfd31.

Authors

Jinfu Lin¹, Hongxia Liu¹, Shulong Wang¹

Affiliation

¹ The Key Laboratory for Wide Bandgap Semiconductor Materials and Devices of Education, School of Microelectronics, Xidian University, Xi'an 710071, People's Republic of China.

PMID: 37751722
DOI: 10.1088/1361-6528/acfd31

Abstract

The potential of neuromorphic computing in synaptic simulation has led to a renewed interest in memristor. However, the demand for multilevel resistive switching with high reliability and low power consumption is still a great resistance in this application. In this work, the electronic synaptic plasticity and simulated bipolar switching behavior of Pt/Al₂O₃(2 nm)/HfO₂(10 nm)/Al₂O₃(2 nm)/Ti tri-layer memristor is investigated. The effect of Al₂O₃layer embedded at the top electrode and the bottom electrode on the resistive performance of the memristor was studied. It is found that both of them can effectively improve the reliability of the device (10⁴cycles), the resistive window (>10³), the tunable synaptic linearity and reduce of the operating voltage. RRAM with Al₂O₃embedded at the top electrode have higher uniformity and LTP linearity, while those with Al₂O₃embedded at the bottom electrode significantly reduce the operating current (∼10μA) and improve LTD linearity. Electron transport mechanisms were compared between single-layer HfO₂and tri-layer Al₂O₃/HfO₂/Al₂O₃samples under DC scanning. The results showed that the thin Al₂O₃layer at the top electrode led to Fowler Northeim tunneling in the low-resistance state, while the thin Al₂O₃layer at the bottom electrode led to Schottky emission in the high-resistance state. The Al₂O₃/HfO₂/Al₂O₃memristors were successfully used to achieve synaptic properties, including enhancement, inhibition, and spike time-dependent plasticity, demonstrating an important role in high-performance neuromorphic computing applications.

Keywords: HfO2; electronic synapse; interface engineering; memristor; multilevel resistive switching.