{"title":"Nanoscaffold Ba0.6Sr0.4TiO3:Nd2O3 ferroelectric memristors crossbar array for neuromorphic computing and secure encryption","authors":"Weifeng Zhang, Jikang Xu, Yongrui Wang, Yinxing Zhang, Yu Wang, Pengfei Li, Yongqing Jia, Zhen Zhao, Changliang Li, Biao Yang, Yue Hou, Zhenqiang Guo, Zeze Huang, Yincheng Qi, Xiaobing Yan","doi":"10.1016/j.jmat.2025.101051","DOIUrl":null,"url":null,"abstract":"Recent advancements in AI have spurred interest in ferroelectric memristors for neuromorphic chips due to their ability to precisely control resistive states through polarization flip-flop without electroforming. However, oxygen vacancies in these devices often cause high leakage current, low endurance, and dispersed switching voltages. Here, we introduce a silicon-based integrated (Ba<sub>0.6</sub>Sr<sub>0.4</sub>TiO<sub>3</sub>)<sub>0.5</sub>(Nd<sub>2</sub>O<sub>3</sub>)<sub>0.5</sub> (BSTN) nanoscaffolded ferroelectric thin film memristor with a vertically self-assembled nanocomposite structure (VSNs) optimally oriented on La<sub>0.67</sub>Sr<sub>0.33</sub>MnO<sub>3</sub>/SrTiO<sub>3</sub>/P–Si substrates. This device demonstrates a widely tunable ferroelectric domain range (0°–180°), high remnant polarization (21.04 μC/cm<sup>2</sup>), and a greater number of unitary states (16 states or 4 bits). It exhibits high durability, enduring over 10<sup>9</sup> switching cycles. The switching mechanism combines ferroelectric polarization and oxygen vacancy migration, enabling the simulation of biological synaptic functions via bi-directional conductance tunability. Additionally, we implemented a low-power (0.57 pJ per event) multi-factor secure encryption system for smart locks using 16×16 BSTN memristor crossbar arrays and a pressure sensor. Under multiple factors (disordered inputs, specific users, and corresponding passwords) the system recognized passwords with 97.6% accuracy and a 3.8% loss rate after 500 iterations. Overall, this work establishes a robust foundation for advancing multilevel storage, neuromorphic computing, and AI chip applications based on ferroelectric memristors.","PeriodicalId":16173,"journal":{"name":"Journal of Materiomics","volume":"5 1","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Materiomics","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1016/j.jmat.2025.101051","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Recent advancements in AI have spurred interest in ferroelectric memristors for neuromorphic chips due to their ability to precisely control resistive states through polarization flip-flop without electroforming. However, oxygen vacancies in these devices often cause high leakage current, low endurance, and dispersed switching voltages. Here, we introduce a silicon-based integrated (Ba0.6Sr0.4TiO3)0.5(Nd2O3)0.5 (BSTN) nanoscaffolded ferroelectric thin film memristor with a vertically self-assembled nanocomposite structure (VSNs) optimally oriented on La0.67Sr0.33MnO3/SrTiO3/P–Si substrates. This device demonstrates a widely tunable ferroelectric domain range (0°–180°), high remnant polarization (21.04 μC/cm2), and a greater number of unitary states (16 states or 4 bits). It exhibits high durability, enduring over 109 switching cycles. The switching mechanism combines ferroelectric polarization and oxygen vacancy migration, enabling the simulation of biological synaptic functions via bi-directional conductance tunability. Additionally, we implemented a low-power (0.57 pJ per event) multi-factor secure encryption system for smart locks using 16×16 BSTN memristor crossbar arrays and a pressure sensor. Under multiple factors (disordered inputs, specific users, and corresponding passwords) the system recognized passwords with 97.6% accuracy and a 3.8% loss rate after 500 iterations. Overall, this work establishes a robust foundation for advancing multilevel storage, neuromorphic computing, and AI chip applications based on ferroelectric memristors.
期刊介绍:
The Journal of Materiomics is a peer-reviewed open-access journal that aims to serve as a forum for the continuous dissemination of research within the field of materials science. It particularly emphasizes systematic studies on the relationships between composition, processing, structure, property, and performance of advanced materials. The journal is supported by the Chinese Ceramic Society and is indexed in SCIE and Scopus. It is commonly referred to as J Materiomics.