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Superstrength permanent magnets with iron-based superconductors by data- and researcher-driven process design

Physics

Superstrength permanent magnets with iron-based superconductors by data- and researcher-driven process design

A. Yamamoto, S. Tokuta, et al.

This groundbreaking research by Akiyasu Yamamoto and colleagues reveals how machine learning can optimize the microstructures of iron-based high-temperature superconductors, resulting in the creation of a Ba0.6K0.4Fe2As2 permanent magnet with a magnetic field strength 2.7 times greater than prior models. Discover how this innovation paves the way for superstrength quasipermanent magnets and advances in superconductivity!

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Playback language: English
Abstract
Iron-based high-temperature superconductors (IBSs) offer potential for next-generation superstrength quasipermanent magnets. However, anisotropic pairing and short coherence lengths hinder supercurrent transport at grain boundaries. This study uses machine learning to manipulate polycrystalline microstructures, resulting in a Ba0.6K0.4Fe2As2 permanent magnet with a magnetic field 2.7 times stronger than previously reported. High-density defects and bipolarized grain boundary spacing distributions contribute to the magnet's strength and stability exceeding 0.1 ppm/h for a 1.5 T magnet.
Publisher
NPG Asia Materials
Published On
Mar 01, 2024
Authors
Akiyasu Yamamoto, Shinnosuke Tokuta, Akimitsu Ishii, Akinori Yamanaka, Yusuke Shimada, Mark D. Ainslie
Tags
iron-based superconductors
machine learning
magnetic field
Ba0.6K0.4Fe2As2
supercurrent transport
defects
grain boundaries
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