Scanning Thermal Microscopy Method for Self-Heating in Nonlinear Devices and Application to Filamentary Resistive Random-Access Memory

Devices with a highly nonlinear resistance-voltage relationship are candidates for neuromorphic computing, which can be achieved by highly temperature dependent processes like ion migration. To explore the thermal properties of such devices, Scanning Thermal Microscopy (SThM) can be employed. However, due to the nonlinearity, the high resolution and quantitative method of AC-modulated SThM cannot readily be used. To this end, an extended nonequilibrium scheme for temperature measurement using SThM is proposed, with which the self-heating of nonlinear devices is studied without the need for calibrating the tip-sample contact for a specific material combination, geometry or roughness. Both a DC and an AC voltage are applied to the device, triggering a periodic temperature rise, which enables the simultaneous calculation of the tip-sample thermal resistance and the device temperature rise. The method is applied to HfO<sub>2</sub>-based RRAM devices, in which the kinetic processes of filamentary switching are governed by temperature. We image temperature and propagation of thermal waves and extract properties like the number of current filaments, thermal confinement and thermal cross-talk.

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Publication Details

Journal
ACS Nano
Published
2025-01-29
DOI
https://doi.org/10.1021/acsnano.4c12784
Citations
8
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
5.84

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article

Scanning Thermal Microscopy Method for Self-Heating in Nonlinear Devices and Application to Filamentary Resistive Random-Access Memory

Nele Harnack, Bernd Gotsmann, Sophie Rodehutskors
8 citations
ACS Nano
Advanced Memory and Neural Computing
5.84
article

Scanning Thermal Microscopy Method for Self-Heating in Nonlinear Devices and Application to Filamentary Resistive Random-Access Memory

Nele Harnack, Bernd Gotsmann, Sophie Rodehutskors
article en
8 citations

Abstract

Devices with a highly nonlinear resistance-voltage relationship are candidates for neuromorphic computing, which can be achieved by highly temperature dependent processes like ion migration. To explore the thermal properties of such devices, Scanning Thermal Microscopy (SThM) can be employed. However, due to the nonlinearity, the high resolution and quantitative method of AC-modulated SThM cannot readily be used. To this end, an extended nonequilibrium scheme for temperature measurement using SThM is proposed, with which the self-heating of nonlinear devices is studied without the need for calibrating the tip-sample contact for a specific material combination, geometry or roughness. Both a DC and an AC voltage are applied to the device, triggering a periodic temperature rise, which enables the simultaneous calculation of the tip-sample thermal resistance and the device temperature rise. The method is applied to HfO<sub>2</sub>-based RRAM devices, in which the kinetic processes of filamentary switching are governed by temperature. We image temperature and propagation of thermal waves and extract properties like the number of current filaments, thermal confinement and thermal cross-talk.

ACS NanoVol. 19(5)
IBM Research - Zurich (CH)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, H2020 Marie Skłodowska-Curie Actions
Affordable and clean energy
Openalex Percentile: Top 4%
Advanced Memory and Neural Computing
5.84
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