Article Analysis of the effect of the Fermi surface matching at Co–Fe and Cu interface on giant magnetoresistance effect using a combinatorial technique

Varun Kumar Kushwaha ORCID (National Institute for Materials Science) ; Ryo Toyama SAMURAI ORCID (National Institute for Materials ScienceROR) ; Yoshio Miura SAMURAI ORCID (National Institute for Materials ScienceROR) ; Yuma Iwasaki SAMURAI ORCID (National Institute for Materials ScienceROR) ; Yuya Sakuraba SAMURAI ORCID (National Institute for Materials ScienceROR)

Varun Co-Fe Cu CIP-GMR AIP Advances (2024).pdf
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Varun Kumar Kushwaha, Ryo Toyama, Yoshio Miura, Yuma Iwasaki, Yuya Sakuraba. Analysis of the effect of the Fermi surface matching at Co–Fe and Cu interface on giant magnetoresistance effect using a combinatorial technique. AIP Advances. 2024, 14 (12), 125329. https://doi.org/10.1063/5.0216909
SAMURAI

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(abstract)

Interfacial electronic band-matching (EBM) plays a crucial role in determining the spin-dependent transport properties and performance of spintronic devices. The final goal of this study is to establish a method to search for new material combinations that exhibit favorable EBM at the interfaces to achieve a superior performance in various spintronic devices using the machine learning technique combined with the first-principles calculations. As a first step, we investigate the effect of interfacial EBM on magnetoresistance (MR) by fabricating the currentin- plane giant magnetoresistive devices with compositionally graded Co1−xFex layers and Cu spacer. The MR ratio varies significantly across x = 0.11–1.0, with the highest MR of 17.5% observed at x = 0.46, followed by a sharp decrease beyond x = 0.6. To analyze the x dependence of MR in terms of EBM with low computational cost, we calculate the simple Fermi surfaces of bcc Co1−xFex and Cu and evaluate the wave
number (k) distance between their Fermi surfaces. The closest (furthest) Fermi surface match occurs at x = 0.4 (1.0), which tends to be in good agreement with the observed MR trend. This suggests that a simple Fermi surface similarity analysis, when integrated

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Keyword: spintronics, giant magnetoresistance, machine learning, Fermi surface, interfacial electronic band matching

Date published: 2024-12-01

Publisher: AIP Publishing

Journal:

  • AIP Advances (ISSN: 21583226) vol. 14 issue. 12 125329

Funding:

  • Japan Society for the Promotion of Science 19K05249
  • Core Research for Evolutional Science and Technology JPMJCR21O1
  • MEXT Program JPMXP1122715503

Manuscript type: Publisher's version (Version of record)

MDR DOI:

First published URL: https://doi.org/10.1063/5.0216909

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Updated at: 2025-01-07 16:30:50 +0900

Published on MDR: 2025-01-07 16:30:50 +0900

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