Effect of Oxygen Vacancy on the Conduction Modulation Linearity and Classification Accuracy of Pr_0.7Ca_0.3MnO₃ Memristor

Abstract

An amorphous Pr0.7Ca0.3MnO3 (PCMO) film was grown on a TiN/SiO2/Si (TiN–Si) substrate at 300 °C and at an oxygen pressure (OP) of 100 mTorr. This PCMO memristor showed typical bipolar switching characteristics, which were attributed to the generation and disruption of oxygen vacancy (OV) filaments. Fabrication of the PCMO memristor at a high OP resulted in nonlinear conduction modulation with the application of equivalent pulses. However, the memristor fabricated at a low OP of 100 mTorr exhibited linear conduction modulation. The linearity of this memristor improved because the growth and disruption of the OV filaments were mostly determined by the redox reaction of OV owing to the presence of numerous OVs in this PCMO film. Furthermore, simulation using a convolutional neural network revealed that this PCMO memristor has enhanced classification performance owing to its linear conduction modulation. This memristor also exhibited several biological synaptic characteristics, indicating that an amorphous PCMO thin film fabricated at a low OP would be a suitable candidate for artificial synapses.

Keywords

• Pr_0.7Ca_0.3MnO₃
• memristor
• resistive switching memory
• convolutional neural network