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Why Does Undoped FeSe Become a High-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mi>T</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:math>Superconductor under Pressure?

2009· article· lv· W2000392967 on OpenAlexaff
Takashi Imai, K. Ahilan, Fanlong Ning, Tyrel M. McQueen, R. J. Cava

Bibliographic record

VenuePhysical Review Letters · 2009
Typearticle
Languagelv
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsMcMaster UniversityCanadian Institute for Advanced Research
Fundersnot available
KeywordsAntiferromagnetismSuperconductivityCondensed matter physicsSpin (aerodynamics)PhysicsMaterials scienceCrystallographyChemistryThermodynamics

Abstract

fetched live from OpenAlex

Unlike the parent phases of the iron-arsenide high-Tc superconductors, undoped FeSe is not magnetically ordered and exhibits superconductivity with Tc approximately 9 K. Equally surprising is the fact that applied pressure dramatically enhances the modest Tc to approximately 37 K. We investigate the electronic properties of FeSe using 77Se NMR to search for the key to the superconducting mechanism. We demonstrate that the electronic properties of FeSe are very similar to those of electron-doped FeAs superconductors, and that antiferromagnetic spin fluctuations are strongly enhanced near Tc. Furthermore, applied pressure enhances spin fluctuations. Our findings suggest a link between spin fluctuations and the superconducting mechanism in FeSe.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.282
Teacher spread0.256 · 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

Citations404
Published2009
Admission routes1
Has abstractyes

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