JOURNAL ARTICLE

The study on non-uniform strain failure of YBa2Cu3O7−δ coated conductors with high critical current.

  • Published In: Modern Physics Letters B, 2025, v. 39, n. 21. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Huang, Zhiting; Qian, Chengcheng; Su, Xiyang; Zhou, Jun; Zhang, Xingyi 3 of 3

Abstract

The YBa2Cu3 O 7 − δ (YBCO)-coated conductors (CCs) exhibit great potential in the manufacturing of ultrahigh field magnets, superconducting fault current limiter, etc., while the irreversible strain plays a crucial role in designing and optimizing the superconducting devices. However, it is a big challenge to obtain the strain dependence of critical current ( I c ) of the coated conductor YBCO CC (width = 10 mm, critical current > 500 A) because of easy destruction induced by strain concentration near the grips in the process of tension. In addition, factors such as non-uniform deformation, contact resistance, and even mechanoelectrical coupling effect, which can induce non-uniform performance degradation, will be huge barriers against the accurate measurement of irreversible strain. In this paper, the failure phenomena and inducement analysis are studied, and an optimized experimental program is proposed based on the test and finite element analysis, which reduces the measuring errors caused by some unfavorable factors. At the end, the complete electrical performance degradation curve of YBCO CC with high I c is given. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Modern Physics Letters B. 2025/07, Vol. 39, Issue 21, p1
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2025
  • ISSN:0217-9849
  • DOI:10.1142/S0217984925500599
  • Accession Number:185260389
  • Copyright Statement:Copyright of Modern Physics Letters B is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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