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Updated: Mar 11, 2026

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Artificial synaptic behaviors of a mobile silver-doped vanadium-cerium oxide memristor with embedded silver
Jiyeon Ryu1, Peter Hayoung Chung1, Cheolhwan Yoon2
1Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea. tsyoon@unist.ac.kr.
Abstract:
Although mobile metal-ion-based filamentary memristors are explored as an artificial synapse for neuromorphic computing, they suffer from abrupt and stochastic switching. Hence, this study reports a non-filamentary synaptic memristor using mobile silver-doped vanadium-cerium oxide (VCeOx:Ag) that achieves linear and symmetric conductance modulation with stable endurance over 104 potentiation/depression cycles through a conduction combined with Ag nanoclusters and redistributed mobile Ag ions. This conjugated contribution enables polarity-dependent, robust and reproducible analog switching. Transmission electron microscopy (TEM) analysis confirms the presence of Ag nanoclusters, and Kelvin probe force microscopy (KPFM) verifies the field-driven migration and redistribution of residual Ag ions. Time-dependent synaptic plasticity properties, including paired-pulse facilitation (PPF), post-tetanic potentiation (PTP), spike-rate-dependent plasticity (SRDP) and short-term-to-long-term memory (STM-to-LTM) transitions, are harnessed to implement reservoir computing (RC), which achieves classification accuracies of 90.6% and 76.7% for handwritten digit-MNIST and Fashion-MNIST datasets, respectively. These findings highlight that the VCeOx:Ag memristor with a complementary mechanism enables an unprecedented control of analog conductance and paves the way for developing scalable, energy-efficient neuromorphic hardware for edge artificial intelligence (AI) and on-device learning.

