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Record W20547476 · doi:10.1021/ic200619c

On the Oxidation of EuFe<sub>4</sub>Sb<sub>12</sub> and EuRu<sub>4</sub>Sb<sub>12</sub>

2011· article· en· W20547476 on OpenAlexafffund
Jessica M. Peddle, Michael W. Gaultois, Andrew P. Grosvenor

Bibliographic record

VenueInorganic Chemistry · 2011
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaBasic Energy SciencesUniversity of WashingtonU.S. Department of Energy
KeywordsSkutteruditeChemistryXANESThermoelectric effectRare earthTransition metalThermal stabilityMetalThermoelectric materialsCrystallographyMineralogyThermodynamicsSpectroscopyPhysicsCatalysis

Abstract

fetched live from OpenAlex

Rare-earth-filled transition-metal pnictides having the skutterudite-type structure have been proposed for use as high-temperature thermoelectric materials to recover waste heat from vehicle exhaust, among other applications. A previous investigation by this research group of one of the most studied skutterudites, CeFe(4)Sb(12), found that, when exposed to air, this material oxidized at temperatures that are considerably below the proposed maximum operating temperature. Here, by the combined use of TGA, powder XRD, and XANES, it has been found that the substitution of Ce(3+) and Fe(2+) for larger rare-earth and transition-metal elements (Eu(2+) and Ru(2+)) results in a significantly higher oxidation temperature compared to that of CeFe(4)Sb(12). This increase can be related to the increased orbital overlap provided by these larger atoms (Eu(2+) and Ru(2+) vs Ce(3+) and Fe(2+)), enabling the development of stronger bonds. These results show how selective substitution of the constituent elements can significantly improve the thermal stability of 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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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

Citations7
Published2011
Admission routes2
Has abstractyes

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