Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Matthew Flynn-Hepford; John Lasseter; Ivan Kravchenko; Steven Randolph; Jong Keum; Bobby G. Sumpter; Stephen Jesse; Petro Maksymovych; A. Alec Talin; Matthew J. Marinella; Philip D. Rack; Anton V. Ievlev; Olga S. Ovchinnikova

doi:10.1002/aelm.202300589

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Matthew Flynn-Hepford, John Lasseter, Ivan Kravchenko, Steven Randolph, Jong Keum, Bobby G. Sumpter, Stephen Jesse, Petro Maksymovych, A. Alec Talin, Matthew J. Marinella, Philip D. Rack, Anton V. Ievlev, Olga S. Ovchinnikova

Research output: Contribution to journal › Article › peer-review

Abstract

Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

Original language	English
Article number	2300589
Journal	Advanced Electronic Materials
Volume	10
Issue number	1
DOIs	https://doi.org/10.1002/aelm.202300589
State	Published - Jan 2024
Externally published	Yes

Funding

This research was funded by the DOE Office of Science Research Program for Microelectronics Codesign (sponsored by ASCR, BES, HEP, NP, and FES) through the Abisko Project with program managers Robinson Pino (ASCR). Hal Finkel (ASCR), and Andrew Schwartz (BES). C-AFM, KPFM, ToF-SIMS and DFT calculations were conducted at the Center for Nanophase Materials Sciences (CNMS), which was a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory ORNL and Sandia. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting this article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide licence to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponcered research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan). Sandia National Laboratories is managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under Contract DE-NA-0003525. This research was funded by the DOE Office of Science Research Program for Microelectronics Codesign (sponsored by ASCR, BES, HEP, NP, and FES) through the Abisko Project with program managers Robinson Pino (ASCR). Hal Finkel (ASCR), and Andrew Schwartz (BES). C‐AFM, KPFM, ToF‐SIMS and DFT calculations were conducted at the Center for Nanophase Materials Sciences (CNMS), which was a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory ORNL and Sandia. This manuscript has been authored by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting this article for publication, acknowledges that the US government retains a nonexclusive, paid‐up, irrevocable, worldwide licence to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponcered research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe‐public‐access‐plan). Sandia National Laboratories is managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under Contract DE‐NA‐0003525.

Funders	Funder number
Andrew Schwartz
DOE Office of Science Research Program for Microelectronics Codesign
DOE Public Access Plan
U.S. Department of Energy
Office of Science
Basic Energy Sciences
National Nuclear Security Administration	DE‐NA‐0003525
Advanced Scientific Computing Research
Oak Ridge National Laboratory	DE-AC05-00OR22725
Higher Education Press	DE‐AC05‐00OR22725

Keywords

ReRAM
memristors
tantalum oxide

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10.1002/aelm.202300589

Cite this

Flynn-Hepford, M., Lasseter, J., Kravchenko, I., Randolph, S., Keum, J., Sumpter, B. G., Jesse, S., Maksymovych, P., Talin, A. A., Marinella, M. J., Rack, P. D., Ievlev, A. V., & Ovchinnikova, O. S. (2024). Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging. Advanced Electronic Materials, 10(1), Article 2300589. https://doi.org/10.1002/aelm.202300589

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title = "Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging",

abstract = "Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.",

keywords = "ReRAM, memristors, tantalum oxide",

author = "Matthew Flynn-Hepford and John Lasseter and Ivan Kravchenko and Steven Randolph and Jong Keum and Sumpter, {Bobby G.} and Stephen Jesse and Petro Maksymovych and Talin, {A. Alec} and Marinella, {Matthew J.} and Rack, {Philip D.} and Ievlev, {Anton V.} and Ovchinnikova, {Olga S.}",

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Flynn-Hepford, M, Lasseter, J, Kravchenko, I, Randolph, S, Keum, J , Sumpter, BG , Jesse, S, Maksymovych, P, Talin, AA, Marinella, MJ, Rack, PD, Ievlev, AV & Ovchinnikova, OS 2024, 'Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging', Advanced Electronic Materials, vol. 10, no. 1, 2300589. https://doi.org/10.1002/aelm.202300589

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AU - Flynn-Hepford, Matthew

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AU - Kravchenko, Ivan

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AU - Keum, Jong

AU - Sumpter, Bobby G.

AU - Jesse, Stephen

AU - Maksymovych, Petro

AU - Talin, A. Alec

AU - Marinella, Matthew J.

AU - Rack, Philip D.

AU - Ievlev, Anton V.

AU - Ovchinnikova, Olga S.

PY - 2024/1

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N2 - Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

AB - Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

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Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

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