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Updated: Jan 9, 2026

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Robust multilevel storage characteristics of Al2O3/HfO2/Al2O3trilayer-structured memristor fabricated by atomic layer
Jian Liu1,2, Xiaolong Zhou1, Junjun Ouyang1
1School of Electronic and Electrical Engineering, East China University of Technology, Nanchang 330013, People's Republic of China.
Abstract:
Memristors with multilevel storage capabilities have emerged as promising candidates for high-density memory and neuromorphic computing systems. In this study, a trilayer-structured memristor with an Al2O3/HfO2/Al2O3(3/14/3 nm) dielectric stack was fabricated via atomic layer deposition, sandwiched between Ti and Pt electrodes. The analog switching characteristics of the memristor were systematically investigated through two strategies: adjusting the compliant current (Icc) during the SET process and controlling the RESET-stop voltage (VRESET-stop) in the RESET process. The experimental results indicate thatIccprimarily modulates the values of low resistance states, whereasVRESET-stopmainly influences the values of high resistance states. To validate multilevel storage feasibility,Iccvalues of 0.5, 1, 2.5, and 5 mA andVRESET-stopvoltages of 1.5, 1.7, 2, and 2.3 V were systematically applied. Statistical analysis demonstrated thatVRESET-stopmodulation yields more stable and repeatable resistance states compared toIcctuning. Furthermore, the continuous resistance (or conductance) tuning capability of our fabricated memristor emulates neural network weight updates. This allows trained weights to be directly mapped to the memristor's conductance states, achieving 91.6% accuracy in handwritten digit recognition. This work underscores the significant potential of the Al2O3/HfO2/Al2O3trilayer-structured memristor for high-performance multilevel storage and neuromorphic computing applications.
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