A Robust Memristor Based on Epitaxial Vertically Aligned Nanostructured BaTiO3−CeO2 Films on Silicon. Issue 23 (2nd May 2022)

• Record Type: Journal Article
• Authors: Yan, Xiaobing; He, Haidong; Liu, Gongjie; Zhao, Zhen; Pei, Yifei; Liu, Pan; Zhao, Jianhui; Zhou, Zhenyu; Wang, Kaiyang; Yan, Hongwei
• Is Part Of: Advanced materials. Volume 34:Issue 23(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-02
• Subjects: algebraic operations -- ferroelectric memristors -- neuromorphic computing -- robust endurance -- vertically aligned nanostructures BaTiO3−CeO2 epitaxial structure; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adma.202110343
• Languages: English
• ISSNs: 0935-9648

Abstract

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 La0.67 Sr0.33 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 10 9 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. Abstract : A composite films system consisting of ferroelectric material and dielectric film is proposed as a memristor medium to improve the comprehensive performances of the resistive‐switching behavior, and epitaxial BaTiO3 −CeO2 ferroelectric films on silicon are obtained successfully. The durability of the device is more than 10 9 cycles, and the speed can be lower than 10 ns.