Abstract
This paper describes the fabrication and characterization of Lithium Niobate (LiNbO3) memristor devices that have the ability to be tuned to a specific resistance state within a continuous resistance range. This is essential for programming neuromorphic systems based on memristor crossbars in order to achieve best deep learning capability. The memristor devices were formed using a 42nm layer of LiNbO3 sandwiched between two metal electrodes. I-V curves demonstrate a typical and repeatable memristor characteristic from −3V to 3V. Such devices have a continuous resistance range that has a maximum to minimum resistance ratio of about 100, and the ability to program intermediate resistance states. The results also show the ability to read the device symmetrically with a positive or negative voltage, and strong data retention after the programming phase.
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