In this work, a ZnO-based resistive switching memory device is characterized by using simplified electrical conduction models. The conventional bipolar resistive switching and complementary resistive switching modes are accomplished by tuning the bias voltage condition. The material and chemical information of the device stack including the interfacial layer of TiON is well confirmed by transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) analysis. The device exhibits uniform gradual bipolar resistive switching (BRS) with good endurance and self-compliance characteristics. Moreover, complementary resistive switching (CRS) is achieved by applying the compliance current at negative bias and increasing the voltage at positive bias. The synaptic behaviors such as long-term potentiation and long-term depression are emulated by applying consecutive pulse input to the device. The CRS mode has a higher array size in the cross-point array structure than the BRS mode due to more nonlinear I–V characteristics in the CRS mode. However, we reveal that the BRS mode shows a better pattern recognition rate than the CRS mode due to more uniform conductance update.

The progress of artificial synaptic devices is vital to the realization of the consciousness of effectual bioinspired neuromorphic computing systems. In this study, we fabricated an ITO/ZnO/PTAA/Ag artificial synaptic memristor based on a low-cost solution process. The fabricated device exhibited uniform gradual bipolar resistive switching with excellent endurance and self-rectifying behavior owing to the bilayer heterojunction structure of ZnO/PTAA. The growth of the conducting filament can be efficiently controlled by modulating the current compliance and voltage during the SET process. Modification of conductance states was also observed by simulations to stimuli, which are essential for synaptic function in neuromorphic computing. Various pulse measurements were performed to mimic synaptic behaviors, including long-term potentiation, long-term depression, spike-rate-dependent plasticity, paired-pulse facilitation, and post-tetanic potentiation. Moreover, we reveal that the real device shows an approximately similar pattern recognition rate as the ideal device owing to a more uniform conductance update.

In this paper, we demonstrate a device using a Ni/SiN/BN/p⁺-Si structure with improved performance in terms of a good ON/OFF ratio, excellent stability, and low power consumption when compared with single-layer Ni/SiN/p⁺-Si and Ni/BN/p⁺-Si devices. Its switching mechanism can be explained by trapping and de-trapping via nitride-related vacancies. We also reveal how higher nonlinearity and rectification ratio in a bilayer device is beneficial for enlarging the read margin in a cross-point array structure. In addition, we conduct a theoretical investigation for the interface charge accumulation/depletion in the SiN/BN layers that are responsible for defect creation at the interface and how this accounts for the improved switching characteristics.

Memristors from theoretical origin and resistive switching to electro-optical devices. Coupled electrical and optical stimuli enable neuromorphic and visual computing.