材料科学
五氧化二钽
记忆电阻器
电阻随机存取存储器
光子学
光电子学
逻辑门
非易失性存储器
纳米技术
计算机科学
薄膜
电子工程
电气工程
工程类
电压
作者
Wenxiao Wang,Feifei Yin,Hongsen Niu,Yang Li,Eun‐Seong Kim,Nam‐Young Kim
出处
期刊:Nano Energy
[Elsevier]
日期:2022-12-05
卷期号:106: 108072-108072
被引量:67
标识
DOI:10.1016/j.nanoen.2022.108072
摘要
Photonic in-memory computing exhibits promising potential to address the inherent limitations of traditional von Neumann architecture. In this study, we demonstrate a tantalum pentoxide (Ta2O5 and Ta2O5−x)-based memristor as a non-volatile memory for photonic in-memory computing functions. The active layer of the memristor on a heavily doped N-Si substrate comprises two films of Ta2O5 and Ta2O5−x with a size of 3 × 3 µm2 of which roughness root-mean-square values are 1.25 nm and 1.59 nm, respectively. A controllable electrical behavior transition from write-once-read-many-times (WORM) memory to resistive random-access memory (RRAM) is achieved by changing the depositional sequence. Benefitting from the visible light response, the in situ photonic Boolean logic operations (“AND/OR”) are achieved in the RRAM device by mixing the light and electric signals, and the power consumption of an “AND” or “OR” operation consumes 4.503 nJ and 4.526 nJ, respectively, proving the superior photonic in-memory computing potential. The basic logic “IMPLICATION” operation is implemented by performing electrical regulation in a circuit with two RRAM devices connected in parallel. Finally, a 5 × 5 RRAM array is developed and thereafter, the array-level logic for image processing applications is realized. The proposed tantalum pentoxide-based memristors possess great potential in constructing efficient in-memory computing architectures.
科研通智能强力驱动
Strongly Powered by AbleSci AI