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2019•IEEE Transactions on Electron DevicesRequires access

Insight into Effects of Oxygen Reservoir Layer and Operation Schemes on Data Retention of HfO2-Based RRAM

Linlin Cai, Wangyong Chen, Yudi Zhao, Xiaoyan Liu, Jinfeng Kang, Xing Zhang, Peng Cheng Huang

Open publisher page 20 citations

Abstract

As a promising new generation of nonvolatile memory, HfO2-based resistive random-access memory (RRAM) has attracted extensive research. However, the problem of data retention has prevented its industrial production as embedded memory. In this paper, from the microscopic understanding, a Monte Carlo simulator is developed to investigate the effects of an oxygen reservoir layer (ORL) on the resistance instability of HfO2-based RRAM. The evolution of conductive filaments (CF) during the retention degradation is visualized by our simulation considering the physical mechanisms of oxygen ions absorbed and released by the ORL. The simulation results are further validated with experiments to provide the prediction of retention performance of RRAMs with different ORLs and operation schemes.

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What this paper is about

As a promising new generation of nonvolatile memory, HfO2-based resistive random-access memory (RRAM) has attracted extensive research. However, the problem of data retention has prevented its industrial production as embedded memory. In this paper, from the microscopic understanding, a Monte Carlo simulator is developed to investigate the effects of an oxygen reservoir layer (ORL) on the resistance instability of HfO2-based RRAM. The evolution of conductive filaments (CF) during the retention degradation is visualized by our simulation considering the physical mechanisms of oxygen ions absorbed and released by the ORL. The simulation results are further validated with experiments to provide the prediction of retention performance of RRAMs with different ORLs and operation schemes.

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Available abstract

As a promising new generation of nonvolatile memory, HfO2-based resistive random-access memory (RRAM) has attracted extensive research. However, the problem of data retention has prevented its industrial production as embedded memory. In this paper, from the microscopic understanding, a Monte Carlo simulator is developed to investigate the effects of an oxygen reservoir layer (ORL) on the resistance instability of HfO2-based RRAM. The evolution of conductive filaments (CF) during the retention degradation is visualized by our simulation considering the physical mechanisms of oxygen ions absorbed and released by the ORL. The simulation results are further validated with experiments to provide the prediction of retention performance of RRAMs with different ORLs and operation schemes.

Key concepts: Resistive random-access memory, Data retention, Oxygen, Resistive touchscreen, Monte Carlo method, Computer science, Degradation (telecommunications), Non-volatile memory

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