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Unipolar modulated volatile memristor: Achieving multi-scale plasticity, associative learning, and dynamic reservoir computing
Nano Research 2026, 19(7): 94908641
Published: 22 May 2026
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The von Neumann architecture is nearing its physical limits regarding energy efficiency and parallelism. Consequently, brain-inspired computing hardware is viewed as a crucial solution to address these limitations. This research presents a volatile memristor featuring an Ag/Al2O3/Ti/Al2O3/ITO configuration for applications in brain-inspired computing. The device demonstrates conductivity modulation under unipolar pulses, attributed to the dynamic competition between electric field-driven drift and heat-induced diffusion, governed by the oxygen vacancy reservoir formed by the in situ oxidized Ti interlayer. The device exhibits multi-scale plasticity, encompassing short-term facilitation (STF), paired-pulse facilitation (PPF), and dependence on frequency and duty cycle. Switching between potentiation and depression can be achieved under the same polarity by tuning the strength of forward stimulation (amplitude, width, or interval). The device emulates the classical conditioned reflex of the spotted butterfly and establishes a dynamic reservoir, attaining accuracies of 97.05% and 83.22% in the MNIST and Fashion-MNIST image recognition tasks, with normalized mean square errors (NMSE) for the two second-order nonlinear system tasks of approximately 0.123 and 0.108, respectively. This study outlines a methodology for fabricating unipolar volatile memristors, thus enhancing the understanding of brain-inspired computing hardware.

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