The DOI matches its Crossref record.
High-Tc superconducting materials for electric power applications
Overview
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Citations
Cited by
Alternative energy technologies
Dresselhaus, M. S., & Thomas, I. L. (2001) · Nature · doi:10.1038/35104599 · Cited by 4,894
Materials science challenges for high-temperature superconducting wire
Foltyn, S. R., Civale, L., MacManus-Driscoll, J. L., Jia, Q. X., Maiorov, B., Wang, H., & Maley, M. (2007) · Nature Materials · doi:10.1038/nmat1989 · Cited by 773
Metadata
- Authors
- Larbalestier, D., Gurevich, A., Feldmann, D. M., & Polyanskii, A.
- Venue
- Materials for Sustainable Energy
- Published
- 2010-10
- Pages
- 311-320
- OpenAlex
- W4236949229
- Cited by
- 924
- References
- 0
- FWCI
- 217.65
- Type
- book chapter
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: High-Tc superconducting materials for electric power applications. https://app.cochat.ai/papers/10.1142/9789814317665_0046
- The paper
- Larbalestier, D., Gurevich, A., Feldmann, D. M., & Polyanskii, A. (2010). High-Tc superconducting materials for electric power applications. Materials for Sustainable Energy. https://doi.org/10.1142/9789814317665_0046
Data sources
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.