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    Yue Ning, Yunfeng Lai, Jiandong Wan, Shuying Cheng, Qiao Zheng, Jinling Yu. Implementation of synaptic learning rules by TaOx memristors embedded with silver nanoparticlesJ. Chin. Phys. B, 2021, 30(4): 047301.
    Yue Ning, Yunfeng Lai, Jiandong Wan, Shuying Cheng, Qiao Zheng, Jinling Yu. Implementation of synaptic learning rules by TaOx memristors embedded with silver nanoparticlesJ. Chin. Phys. B, 2021, 30(4): 047301.
  • Implementation of synaptic learning rules by TaOx memristors embedded with silver nanoparticles

    • As an alternative device for neuromorphic computing to conquer von Neumann bottleneck, the memristor serving as an artificial synapse has attracted much attention. The TaOx memristors embedded with silver nanoparticles (Ag NPs) have been fabricated to implement synaptic plasticity and to investigate the effects of Ag NPs. The TaOx memristors with and without Ag NPs are capable of simulating synaptic plasticity (PTP, STDP, and STP to LTP), learning, and memory behaviors. The conduction of the high resistance state (HRS) is driven by Schottky-emission mechanism. The embedment of Ag NPs causes the low resistance state (LRS) conduction governed by a Poole-Frenkel emission mechanism instead of a space-charge-limited conduction (SCLC) in a pure TaOx system, which is ascribed to the Ag NPs enhancing electric field to produce additional traps and to reduce Coulomb potential energy of bound electrons to assist electron transport. Consequently, the enhanced electric fields induced by Ag NPs increase the learning strength and learning speed of the synapses. Additionally, they also improve synaptic sensitivity to stimuli. The linearity of conductance modulation and the reproducibility of conductance are improved as well.
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