MétaCan
Menu
Back to cohort
Record W2017089226 · doi:10.1088/0953-2048/23/5/050201

The electromagnetic properties of iron-based superconductors

2010· article· en· W2017089226 on OpenAlexaff
R. Prozorov, A. Gurevich, G. M. Luke

Bibliographic record

VenueSuperconductor Science and Technology · 2010
Typearticle
Languageen
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSuperconductivityCuprateCondensed matter physicsPhysicsAntiferromagnetismHigh-temperature superconductivityMaterials science

Abstract

fetched live from OpenAlex

Iron-based superconductors, discovered just a few years ago, are members of a diverse family of pnictides and chalcogenides which may potentially contain hundreds of superconducting compounds. The unconventional, multiband superconductivity in these materials most likely emerges from the quintessential magnetic Fe ions. Along with many similarities to the high- T c cuprates, the proximity of antiferromagnetism to superconductivity in these semi-metallic materials has attracted much attention. The massive effort aimed at understanding superconductivity in the high- T c cuprates has stimulated the development of numerous state-of-the-art experimental techniques, improved crystal growth methods and a variety of new theoretical insights. These tools and models were already available and readily applied to the new iron-based superconductors for which lots of high quality new results are being reported literally every day. The current special section represents only a snapshot of these extensive studies performed in the second half of 2009, less than two years after the discovery of 26 K superconductivity in the LaFeAsO compound. The range of various experiments is impressive and this issue is mostly focused on the electromagnetic properties of these iron-based materials. The electromagnetic response is sensitive to the microscopic electronic behavior and therefore can be used to probe the mechanism of superconductivity. On the other hand, it is the electromagnetic response that determines many possible applications of these superconductors, particularly given their extremely high upper critical fields. At this point it is already quite clear that the iron-based superconductors cannot unambiguously fit into any known type of superconductor class and have been placed in one of their own. The metallic ground state of the parent compounds is different from the insulating state of the cuprates and generally exhibits a lower electromagnetic anisotropy. However, similar to the cuprates, a superconducting 'dome' is formed upon doping the parent compounds, which exhibits antiferromagnetic and structural transitions at temperatures well above the superconducting critical temperature. This special section touches on several key aspects of these new iron-based superconductors. These topics include materials synthesis and basic characterization, the role of impurities and pairing symmetry, and mapping of the superconducting phase diagram as a function of chemical doping and pressure. Studies of transport, magnetic and optical properties account for a substantial portion of this special section. Particular attention is devoted to the role of magnetic excitations and the issue of the possible coexistence of magnetism and superconductivity. Attempts to understand the nature of the superconducting pairing are discussed from several angles, including tunneling spectroscopy and the London penetration depth. The vortex state is probed by magnetization, transport and neutron scattering, while the irreversible state is probed by studies of magnetic and transport critical current density.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.242
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSuperconductor Science and TechnologySame topicIron-based superconductors researchFrench-language works237,207