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HfOx-Based Conductive Bridge Random Access Memory with Al2O3 Sandglass Nanostructures via Glancing Angle Deposition Technology toward Neuromorphic Applications
期刊文章

HfOx-Based Conductive Bridge Random Access Memory with Al2O3 Sandglass Nanostructures via Glancing Angle Deposition Technology toward Neuromorphic Applications

Ying-Chun Shen, Yu-Wen Huang, Tzu-Yi Yang, Yi-Jen Yu, Hao-Chung Kuo, Tseung-Yuen TsengYu-Lun Chueh
ACS Applied Nano Materials
2023

摘要

conductive bridge random access memory glancing angle deposition neuromorphic computing system sandglass nanostructures synaptic plasticity thermal enhanced layer Materials Science (all)
Conductive bridge random access memory (CBRAM) is one of the promising nonvolatile memories for next-generation technology owing to its high density, low power consumption, and fast switching speed, which is also a potential candidate for implementation of neuromorphic computing. However, CBRAMs suffer from stochastically growing conducting filaments in the insulator layer. Herein, we demonstrated Al <sub>2</sub> O <sub>3</sub> sandglass nanostructures (SNGSs) embedded into HfO <sub>x</sub> -based CBRAMs via glancing angle deposition technology with the AlN thermal enhanced layer to prevent the overinjection of cations and localize the growth of conducting filaments in the HfO <sub>x</sub> switching layer. With the assistance of Al <sub>2</sub> O <sub>3</sub> SNGSs and the AlN layer, the Cu/Al <sub>2</sub> O <sub>3</sub> SNGSs/HfO <sub>x</sub> /AlN/TiN device exhibited a stable on/off ratio of >10 for more than 6000 cycles. Furthermore, with a Te top electrode, the Te/Al <sub>2</sub> O <sub>3</sub> SNGSs/HfO <sub>x</sub> /AlN/TiN device shows a multilevel cell characteristic by controlling compliance currents. In addition, it possesses excellent potentiation and depression nonlinearities of 1.28 and 0.4, respectively, which is beneficial for future applications in neuromorphic computing.

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