HfO2/TiOx bilayer structure memristor with linear conductance tuning for high density memory and neuromorphic computing

• Published in: Journal of applied physics 2020-11, Vol.128 (18)
• Main Authors: Liu, Jian, Yang, Huafeng, Ma, Zhongyuan, Chen, Kunji, Huang, Xinfan, Wang, Ke
• Format: Article
• Language: English
• Subjects: Applied physics; Computation; Computer memory; Data storage; Density; Fault tolerance; Hafnium oxide; Memristors; Neuromorphic computing; Pulse amplitude; Resistance; Titanium oxides; Tuning; Voltage pulses
• ISSN: 0021-8979; 1089-7550
• DOI: 10.1063/5.0024668

Memristors with tunable conductance characteristics have attracted great attention in high density memory and neuromorphic computing. However, the dynamics of conductance change for filamentary-type memristors is generally asymmetric: The set transition is quite abrupt, while the reset transition is usually gradual, which is a big challenge to achieve continuous conductance tuning characteristics in both set and reset processes. In this work, we demonstrated an HfO2/TiOx (10 nm/10 nm) bilayer structure memristor with the feature of bidirectional conductance tuning (a gradual increase or decrease in conductance) in a simple pulse-train operation mode. A series of voltage pulses with specific amplitude and a fixed width of 50 ns were used to realize the characteristics of bidirectional conductance tuning. By further optimizing the pulse amplitude conditions, such as −1.1 V/50 ns for the set process and 1.3–1.4 V/50 ns for the reset process, the conductance of the memristor can be tuned almost linearly with the input pulse voltage. Such linear conductance update is highly desired for improving the fault tolerance ability in massive data storage or neuromorphic computing.