Parametric study of “filament and gap” models of resistive switching in TaOx-based devices.

A finite element model consisting of a conducting filament with or without a gap was used to reproduce the behavior of TaOx-based resistive switching devices. The specific goal was to explore the range of possible filament parameters such as filament diameter, composition, gap width, and composition to reproduce the conductance and shape of I–V while keeping the maximum temperature within the acceptable range allowing for ion motion and preventing melting. The model solving heat and charge transport produced a good agreement with experimental data for the oxygen content in the filament below TaO1.3, the filament diameter range between 6 and 22 nm, and the gap oxygen content between TaO1.7 and TaO1.85. Gap width was not limited to either low or high sides according to the criteria considered in this report. The obtained filament composition corresponds to oxygen deficiency an order of magnitude higher than one estimated by other modeling efforts. This was in large part due to the use of recent experimental values of conductivity as a function of composition and temperature. Our modeling results imply that a large fraction of atoms leaves and/or accumulates within the filament to produce a large relative concentration change. This, in turn, necessitates the inclusion of strain energy in the filament formation modeling. In addition, the results reproduce non-linear I–V without the necessity of assuming the Poole–Frenkel type of electrical conduction or the presence of a barrier at the oxide/metal interface.

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Publication Details

Journal
Journal of Applied Physics
Published
2025-03-19
DOI
https://doi.org/10.1063/5.0246985
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92

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article

Parametric study of “filament and gap” models of resistive switching in TaOx-based devices.

Rongchen Li, Yang Bai, Marek Skowroński
4 citations
Journal of Applied Physics
Advanced Memory and Neural Computing
2.92
article

Parametric study of “filament and gap” models of resistive switching in TaOx-based devices.

Rongchen Li, Yang Bai, Marek Skowroński
article en
4 citations

Abstract

A finite element model consisting of a conducting filament with or without a gap was used to reproduce the behavior of TaOx-based resistive switching devices. The specific goal was to explore the range of possible filament parameters such as filament diameter, composition, gap width, and composition to reproduce the conductance and shape of I–V while keeping the maximum temperature within the acceptable range allowing for ion motion and preventing melting. The model solving heat and charge transport produced a good agreement with experimental data for the oxygen content in the filament below TaO1.3, the filament diameter range between 6 and 22 nm, and the gap oxygen content between TaO1.7 and TaO1.85. Gap width was not limited to either low or high sides according to the criteria considered in this report. The obtained filament composition corresponds to oxygen deficiency an order of magnitude higher than one estimated by other modeling efforts. This was in large part due to the use of recent experimental values of conductivity as a function of composition and temperature. Our modeling results imply that a large fraction of atoms leaves and/or accumulates within the filament to produce a large relative concentration change. This, in turn, necessitates the inclusion of strain energy in the filament formation modeling. In addition, the results reproduce non-linear I–V without the necessity of assuming the Poole–Frenkel type of electrical conduction or the presence of a barrier at the oxide/metal interface.

Journal of Applied PhysicsVol. 137(11)
Carnegie Mellon University (US)
National Science Foundation, Division of Materials Research
Openalex Percentile: Top 10%
Advanced Memory and Neural Computing
2.92
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Parametric study of “filament and gap” models of resistive switching in TaOx-based devices. — Rongchen Li, Yang Bai, et al. · Journal of Applied Physics (2025) | TGRS Research Map | TGRS