A Robust Memristor Based on Epitaxial Vertically Aligned Nanostructured BaTiO₃ -CeO₂ Films on Silicon.

Abstract

With the exploration of ferroelectric materials, researchers have a strong desire to explore the next generation of non-volatile ferroelectric memory with silicon-based epitaxy, high-density storage, and algebraic operations. Herein, a silicon-based memristor with an epitaxial vertically aligned nanostructures BaTiO₃ -CeO₂ film based on La_0.67 Sr_0.33 MnO₃ /SrTiO₃ /Si substrate is reported. The ferroelectric polarization reversal is optimized through the continuous exploring of growth temperature, and the epitaxial structure is obtained, thus it improves the resistance characteristic, the multi-value storage function of five states is achieved, and the robust endurance characteristic can reach 10⁹ cycles. In the synapse plasticity modulated by pulse voltage process, the function of the spiking-time-dependent plasticity and paired-pulse facilitation is simulated successfully. More importantly, the algebraic operations of addition, subtraction, multiplication, and division are realized by using fast speed pulse of the width ≈50 ns. Subsequently, a convolutional neural network is constructed for identifying the CIFAR-10 dataset, to simulate the performance of the device; the online and offline learning recognition rate reach 90.03% and 92.55%, respectively. Overall, this study paves the way for memristors with silicon-based epitaxial ferroelectric films to realize multi-value storage, algebraic operations, and neural computing chip applications.