Thermoelectric fingerprinting of Bloch- and Néel-type skyrmions

Magnetic skyrmions are nanoscale spin textures that exhibit topological stability, which, along with their thermal and electrical transport properties, make them the ideal candidates for a variety of technological applications. Accessing the skyrmion spin texture at the nanoscale and understanding its interaction with local thermal gradients is essential for engineering skyrmion-based transport phenomena. However, direct experimental insight into the local thermoelectric response of single skyrmions remains limited. To address this, we employ scanning thermoelectric microscopy (SThEM) to probe the nanoscale thermoelectric response from a single skyrmion. By mapping the local thermoelectric voltage with nanoscale precision, we reveal a unique spatially resolved response that is the convolution of the underlying spin texture of the skyrmion and its interaction with the highly localized thermal gradient originating from the heated probe. We combine this with thermoelectric modelling of a range of skyrmion spin textures to reveal unique thermoelectric responses and allow the possibility of SThEM to be used as a tool to distinguish nanoscale spin textures. These findings provide fundamental insights into the interaction of topologically protected spin textures with local thermal gradients and the resultant spin transport. We demonstrate a route to thermally characterize nanoscale spin textures, accelerating the material optimization cycle, while also opening the possibility to harness skyrmions for spin caloritronics.

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Publication Details

Journal
Applied Physics Letters
Published
2025-10-13
DOI
https://doi.org/10.1063/5.0284384
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Thermoelectric fingerprinting of Bloch- and Néel-type skyrmions

Petr Klapetek, Katharina Zeissler, Robert Puttock, Olga Kazakova et al.
1 citations
Applied Physics Letters
Advanced Memory and Neural Computing
0.73
article

Thermoelectric fingerprinting of Bloch- and Néel-type skyrmions

Petr Klapetek, Katharina Zeissler, Robert Puttock, Olga Kazakova, Christopher E. A. Barker, Elías Saugar, O. Chubykalo‐Fesenko, C. H. Marrows, Craig Barton
article en
1 citations

Abstract

Magnetic skyrmions are nanoscale spin textures that exhibit topological stability, which, along with their thermal and electrical transport properties, make them the ideal candidates for a variety of technological applications. Accessing the skyrmion spin texture at the nanoscale and understanding its interaction with local thermal gradients is essential for engineering skyrmion-based transport phenomena. However, direct experimental insight into the local thermoelectric response of single skyrmions remains limited. To address this, we employ scanning thermoelectric microscopy (SThEM) to probe the nanoscale thermoelectric response from a single skyrmion. By mapping the local thermoelectric voltage with nanoscale precision, we reveal a unique spatially resolved response that is the convolution of the underlying spin texture of the skyrmion and its interaction with the highly localized thermal gradient originating from the heated probe. We combine this with thermoelectric modelling of a range of skyrmion spin textures to reveal unique thermoelectric responses and allow the possibility of SThEM to be used as a tool to distinguish nanoscale spin textures. These findings provide fundamental insights into the interaction of topologically protected spin textures with local thermal gradients and the resultant spin transport. We demonstrate a route to thermally characterize nanoscale spin textures, accelerating the material optimization cycle, while also opening the possibility to harness skyrmions for spin caloritronics.

Applied Physics LettersVol. 127(15)
University of Leeds (GB), Central European Institute of Technology (CZ), National Physical Laboratory (GB), University of Manchester (GB), Instituto de Ciencia de Materiales de Madrid (ES), Český metrologický institut (CZ)
Government of the United Kingdom, European Commission, Ministerio de Ciencia e Innovación, Horizon 2020 Framework Programme, Agencia Estatal de Investigación, European Metrology Programme for Innovation and Research
Openalex Percentile: Top 22%
Advanced Memory and Neural Computing
0.73
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