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Record W2504725510 · doi:10.1201/b13727-3

Synthesis and Physical Properties of the New Potassium Iron Selenide Superconductor K0.80Fe1.76Se2

2012· book-chapter· en· W2504725510 on OpenAlexafffund
Rongwei Hu, E. D. Mun, D. H. Ryan, K. Cho, H Kim, Halyna Hodovanets, Warren E. Straszheim, M. A. Tanatar, R. Prozorov, W. N. Rowan‐Weetaluktuk, J. M. Cadogan, Mohammednoor Altarawneh, C. Mielke, Vivien S. Zapf, Sergey L. Bud’ko, P. C. Canfield

Bibliographic record

VenuePan Stanford Publishing eBooks · 2012
Typebook-chapter
Languageen
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsUniversity of ManitobaMcGill University
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of CanadaMultidisciplinary University Research InitiativeCanada Research ChairsAlfred P. Sloan FoundationNational High Magnetic Field LaboratoryNational Science FoundationIowa State UniversityFonds Québécois de la Recherche sur la Nature et les TechnologiesU.S. Department of Energy
KeywordsSelenideSuperconductivityMaterials sciencePotassiumIron-based superconductorCondensed matter physicsMetallurgyPhysicsSelenium

Abstract

fetched live from OpenAlex

LaFeO1−xFx with Tc = 26 K was reported in early 2008. Since then, more than 4,000 papers have been published and the maximum Tc reached 56 K, which is next to high-Tc cuprates. Iron-based superconductors have several unique propertiesmostly arising from their multi-orbital nature. The presence of a vast number of parent materials is a characteristic of this system. This chapter describes the background research to the discovery, the crystal structure and properties of parent materials, and growth of the single crystals and epitaxial thin films.

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 score0.007

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 communication0.0000.001
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 head0.047
GPT teacher head0.241
Teacher spread0.194 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

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