HfO2-Based RRAM with In Situ Conductive Channels Induced by Nanoparticles to Improve Stability
Source abstract
Abstract
Resistive random access memory (RRAM) has emerged as a memory technology due to its simple structure and compatibility with CMOS technology. In recent years, it was reported that HfO 2 -based RRAMs are promising for commercial applications but suffer from a relatively poor performance in stability and retention due to the random formation and breakage of the conductive channels. In this work, we introduced a layer of Ag nanoparticles embedded in the HfO 2 resistive switching layer to address the randomness in HfO 2 -based RRAMs. It was found that the embedding of Ag nanoparticles enhances the local electric field in HfO 2, as a result of which conductive filaments in the RRAM will preferably grow where nanoparticles are located. By controlling the uniformity and distribution of Ag nanoparticles, the resistive switching uniformity is significantly improved. The relative fluctuation of V set is reduced from 13.85 to 6.96%, and the relative fluctuation of V reset is reduced from 23.01 to 14.45%. More importantly, we also achieved strong stability and a large resistive window with an on/off ratio of up to 10 2 . In the end, we proposed a resistive switching model to interpret the experimental observations.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Ocean Information Engineering, Jimei University, Xiamen 361021, Fujian, China
University of Michigan─Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China
Institute of Electromagnetics and Acoustics and Key Laboratory of Electromagnetic Wave Science and Detection Technology, Xiamen University, Xiamen 361005, Fujian, China
Funding
Natural Science Foundation of Fujian Province
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