The CeO2-based memristor has attracted significant attention due to its intrinsic resistive switching (RS) properties, large on/off ratio, and great plasticity, making it a promising candidate for artificial synapses. However, significant challenges such as high power consumption and poor device reliability hinder its broad application in neuromorphic microchips. To tackle these issues, in this work, we design a novel bilayer (BL) memristor by integrating a CeO2-based memristor with a Co-CeO2 vertically aligned nanocomposite (VAN) layer and compare it with the single layer (SL) memristor. Preliminary electrical testing reveals that the BL memristor offers a reduced set/reset voltage (∼67% lower), a higher on/off ratio (∼5 × 102), enhanced device reliability, and improved device-to-device variation compared to the SL memristor. Insight from COMSOL simulation, coupled with microstructural analysis, provides a comprehensive elucidation on how the VAN layer facilitates the selective conductive filament (CF) formation. Subsequently, the plasticity of the BL memristor is evaluated through long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-time-dependent plasticity (STDP). The spiking neural network (SNN) built upon the BL memristor achieves remarkable accuracy (∼94%) after only 12 iterations, underscoring its potential for high-performance neural networks.
Keywords: CeO2; electronic synapse; memristor; neuromorphic computing; vertically aligned nanocomposite.