Diffusion Characteristics of Ru and Oxygen Vacancies in Ta<sub>2</sub>O<sub>5</sub> for Resistive Random Access Memory Devices: A Density Functional Theory Investigation

Abstract The resistive switching behavior of memristors is primarily determined by the characteristics of their mobile species, with balancing retention and switching energy being a significant challenge. Ruthenium (Ru) has recently emerged as a potential mobile species, enabling low switching currents, rapid operation, and good retention, addressing critical issues in next‐generation memory systems. However, understanding the atomistic details of Ru diffusion in oxides remains lacking but critical for interpreting its promising experimental device behavior. Here, we conduct a comprehensive atomistic analysis of Ru and oxygen vacancy (OV) diffusion in Ta 2 O 5 ‐based memristors utilizing density functional theory computations. Our findings reveal that Ru‐doping at interstitial sites demonstrates a noticeably lower diffusion barrier than OVs, signifying improved mobility under an electric field. This underscores the emergence of Ru‐based conductive filaments as a crucial mechanism for memristive switching. Formation energy analyses indicate that Ru ions possess lower formation energies than OVs, improving their thermodynamic stability and mobility within the oxide matrix. Moreover, electronic structure studies reveal significant alterations in the local density of states near the Fermi level around Ru and OV sites, influencing the material's conductive properties. These findings establish a strong basis for optimizing Ru‐based memristive devices for next‐generation memory technologies.

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Publication Details

Journal
Advanced Electronic Materials
Published
2025-05-08
DOI
https://doi.org/10.1002/aelm.202500128
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73
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article

Diffusion Characteristics of Ru and Oxygen Vacancies in Ta2O5 for Resistive Random Access Memory Devices: A Density Functional Theory Investigation

Ajit K. Roy, Md. Sherajul Islam, J. Joshua Yang, Sabyasachi Ganguli
1 citations
Advanced Electronic Materials
Advanced Memory and Neural Computing
0.73
article

Diffusion Characteristics of Ru and Oxygen Vacancies in Ta2O5 for Resistive Random Access Memory Devices: A Density Functional Theory Investigation

Ajit K. Roy, Md. Sherajul Islam, J. Joshua Yang, Sabyasachi Ganguli
article en
1 citations

Abstract

Abstract The resistive switching behavior of memristors is primarily determined by the characteristics of their mobile species, with balancing retention and switching energy being a significant challenge. Ruthenium (Ru) has recently emerged as a potential mobile species, enabling low switching currents, rapid operation, and good retention, addressing critical issues in next‐generation memory systems. However, understanding the atomistic details of Ru diffusion in oxides remains lacking but critical for interpreting its promising experimental device behavior. Here, we conduct a comprehensive atomistic analysis of Ru and oxygen vacancy (OV) diffusion in Ta 2 O 5 ‐based memristors utilizing density functional theory computations. Our findings reveal that Ru‐doping at interstitial sites demonstrates a noticeably lower diffusion barrier than OVs, signifying improved mobility under an electric field. This underscores the emergence of Ru‐based conductive filaments as a crucial mechanism for memristive switching. Formation energy analyses indicate that Ru ions possess lower formation energies than OVs, improving their thermodynamic stability and mobility within the oxide matrix. Moreover, electronic structure studies reveal significant alterations in the local density of states near the Fermi level around Ru and OV sites, influencing the material's conductive properties. These findings establish a strong basis for optimizing Ru‐based memristive devices for next‐generation memory technologies.

Advanced Electronic Materials
University of Southern California (US), Wright-Patterson Air Force Base (US), Spectral Energies (United States) (US)
Openalex Percentile: Top 29%
Advanced Memory and Neural Computing
0.73
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