Artificial synaptic behaviors of a mobile silver-doped vanadium–cerium oxide memristor with embedded silver nanoclusters for neuromorphic computing applications

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 (VCeO_x: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 VCeO_x: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.