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Cited by 400

The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.

Magnetic penetration depth in unconventional superconductors

Open access
Prozorov, Ruslan, Giannetta, Russell W·2006·Superconductor Science and Technology

Abstract

This topical review summarizes various features of magnetic penetration depth in unconventional superconductors. Precise measurements of the penetration depth as a function of temperature, magnetic field and crystal orientation can provide detailed information about the pairing state. Examples are given of unconventional pairing in hole- and electron-doped cuprates, organic and heavy fermion superconductors. The ability to apply an external magnetic field adds a new dimension to measurements of penetration depth. We discuss how field-dependent measurements can be used to study surface Andreev bound states, nonlinear Meissner effects, magnetic impurities, magnetic ordering, proximity effects and vortex motion. We also discuss how measurements of penetration depth as a function of orientation can be used to explore superconductors with more than one gap and with anisotropic gaps. Details relevant to the analysis of penetration depth data in anisotropic samples are also discussed.

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Crossref · 10.1088/0953-2048/19/8/r01

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Metadata

Authors
Prozorov, R., & Giannetta, R. W.
Venue
Superconductor Science and Technology
Published
2006-06-19
Volume
19
Issue
8
Pages
R41-R67
ISSN
  • 0953-2048 (ISSN-L)
  • 1361-6668
OpenAlex
W1963893306
Cited by
400
References
84
FWCI
8.27
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Magnetic penetration depth in unconventional superconductors. https://app.cochat.ai/papers/10.1088/0953-2048/19/8/r01
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Prozorov, R., & Giannetta, R. W. (2006). Magnetic penetration depth in unconventional superconductors. Superconductor Science and Technology. https://doi.org/10.1088/0953-2048/19/8/r01

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.