神经形态工程学
材料科学
钙钛矿(结构)
光电子学
MNIST数据库
记忆电阻器
计算机科学
电子工程
内存处理
肖特基二极管
人工神经网络
纳米电子学
电阻随机存取存储器
CMOS芯片
兴奋剂
非易失性存储器
电阻式触摸屏
电气工程
纳米技术
能源消耗
突触重量
热传导
卷积神经网络
价(化学)
德拉姆
电导率
导电体
物理
作者
Narendar Malishetty,Vaishali Chandmare,Narendar Vadthiya,Hitesh Borkar
摘要
ABSTRACT Neuromorphic computing requires electronic devices capable of stable analogue switching, low energy operation, and reliable synaptic behaviour. In this study, Zinc zirconate (ZZO) and Ti‐doped ZnZrO 3 (TZZO) perovskite thin films were developed to realise high‐performance memristors, and their switching behaviour is correlated with defect chemistry and electronic structure. Resistive switching devices with Ag/ZZO/FTO and Ag/TZZO/FTO configurations exhibit consistent bipolar switching, governed by ohmic, space‐charge‐limited conduction (SCLC), and high‐field‐assisted transport mechanisms associated with Schottky and Poole–Frenkel conduction. The switching behaviour in Ag/TZZO/FTO is primarily attributed to an oxygen‐vacancy‐mediated valence change memory (VCM) mechanism, with possible minor contributions from field‐assisted Ag‐ion migration. These devices showed strong performance, with endurance reaching 10 4 cycles and retention of 10 4 s. Density functional theory (DFT) studies revealed that Ti doping improves electrical conductivity via defect‐driven transport pathways. The neuromorphic computing potential of these devices was validated by integrating their long‐term potentiation and depression (LTP and LTD) behaviours into a convolutional neural network (CNN) trained on the MNIST dataset, achieving digit recognition accuracies of 94.35% for ZZO and 98.35% for TZZO. These results establish the Ti‐doped ZZO as a promising candidate for next‐generation non‐volatile memory and neuromorphic applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI