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Phonon density of states and the search for a resonance mode in LaFeAsO<sub>0.85</sub>F<sub>0.15</sub>(T<sub><i>c</i></sub>= 26 K)

2012· article· en· W1990300657 on OpenAlexaff
Z. Yamani, D. H. Ryan, J. M. Cadogan, F. Canepa, A. Palenzona, A. Orecchini

Bibliographic record

VenueJournal of Physics Conference Series · 2012
Typearticle
Languageen
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsUniversity of ManitobaMcGill UniversityCanadian Nuclear Laboratories
Fundersnot available
KeywordsPairingPhononCondensed matter physicsSuperconductivityInelastic neutron scatteringResonance (particle physics)ExcitationNeutron scatteringScatteringInelastic scatteringMaterials sciencePhysicsAtomic physics

Abstract

fetched live from OpenAlex

While the high transition temperatures suggest that the conventional BCS phononmediated&#13;\nmechanism may not provide the main pairing mechanism in the recently discovered RFeAsO1−xFx (1111-&#13;\ntype) superconductors, there is, as yet, no consensus, despite extensive experimental and theoretical study.&#13;\nWe report here the results of an inelastic neutron scattering investigation of an overdoped polycrystalline&#13;\nsample of LaFeAsO1−xFx with x=0.15 (Tc=26 K). Four excitation peaks were observed at 13.6±1.5,&#13;\n24.2±0.8, 32.2±0.5, and 41.4±1.0 meV. They were identified as phonon modes based on their wavevector and&#13;\ntemperature dependence. The peak positions agree well with first-principles calculations of phonon density&#13;\nof states as well as experimental data on both the insulating parent and optimally doped LaFeAsO1−xFx&#13;\ncompounds. No evidence for the presence of a resonance mode was found. We found that the phonon density&#13;\nof states of the x=0.15 sample remains unchanged below Tc and is similar to samples with other fluorine&#13;\nconcentrations. This suggests that a standard electron-phonon pairing mechanism cannot explain the high&#13;\ntransition temperatures observed in these materials.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.278
Teacher spread0.248 · 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 teacher head, not a consensus.

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

Citations2
Published2012
Admission routes1
Has abstractyes

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