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Updated: Feb 24, 2026

A Method for Growing Bio-memristors from Slime Mold
Published on: November 2, 2017
Dual-Mode MoOx/Al2O3 Memristors with Ultra-Stable Switching Capability for High-Precision Reservoir Computing
Shaojie Fan1, Yuqing Fan1, Fang Wang1
1State Key Laboratory of Crystal Materials, School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic & Communication Devices, Tianjin University of Technology, Tianjin 300384, P. R. China.
None:
Memristors are an innovative electronic gadget that help solve problems with the von Neumann architecture and make it easier to implement neuromorphic computing systems. Both complementary digital memristors and extremely durable analog memristors are necessary for high-performance neuromorphic computing systems. Here, Ag/MoOx/Al2O3/TiN (A-MA-T) structure-based digital-analog integrated memristors are fabricated. The A-MA-T device's electrical characteristics are examined, exhibiting consistent digital-to-analog conversion capabilities. Then, the conversion mechanism is clarified by contrasting different types of electrodes with distinct functional layers. Interestingly, the manufactured A-MA-T gadget used conductance modulation to create artificial synapse emulation, including excitatory postsynaptic current (EPSC), inhibitory postsynaptic current (IPSC), long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation (PPF), and spike-timing-dependent plasticity (STDP). Additionally, the physical model of A-MA-T devices is built and integrated with the RC system, which achieved a recognition rate of 94.67% on the Yale Face Data set. This study offers a framework for achieving a memristor with multifunctional integration.
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