电阻随机存取存储器
记忆电阻器
横杆开关
晶体管
二极管
神经形态工程学
电气工程
材料科学
光电子学
计算机科学
拓扑(电路)
电子工程
工程类
电压
人工智能
人工神经网络
作者
Jayatika Sakhuja,Srinu Rowtu,Shubham Patil,Sandip Lashkare,Udayan Ganguly
出处
期刊:IEEE Electron Device Letters
[Institute of Electrical and Electronics Engineers]
日期:2023-03-15
卷期号:44 (5): 741-744
被引量:1
标识
DOI:10.1109/led.2023.3257430
摘要
Crossbar memristor arrays are gaining interest in the semiconductor industry for high-density storage and in- memory computing applications. For efficient array operations, highly non-linear selector (1S) or transistor (1T) devices are connected in series with memristor devices to rectify sneak path leakage currents. For selector-memristor integration, process and device compatibility is a must. In this work, we have experimentally demonstrated the integration of Pr $_{{0}.{7}}$ Ca $_{{0}.{3}}$ MnO3 (PCMO) based resistive random access memory (RRAM) and Silicon (Si) junction devices. We propose and evaluate various integration schemes for Si-PN junction Diode (1D) and PCMO-RRAM (1R) to identify a successful approach where both devices retain their characteristics after integration. Moreover, the electrical measurements for the integrated 1D1R structure show the SET switching of PCMO-RRAM. Lastly, we show bipolar RRAM switching analogous to 1S1R configuration using an anti-parallel diode connection. The integration approach can be used to design a scaled-1S1R or 1T1R cell for large-scale crossbar memristor arrays with PCMO-RRAM.
科研通智能强力驱动
Strongly Powered by AbleSci AI