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Record W1626329688 · doi:10.1063/1.3086641

Thermoelectric performance of NiyMo3Sb7−xTex (y≤0.1, 1.5≤x≤1.7)

2009· article· en· W1626329688 on OpenAlexafffund
Hongyi Xu, Katja M. Kleinke, Tim Holgate, H. Zhang, Zhe Su, Terry M. Tritt, Holger Kleinke

Bibliographic record

VenueJournal of Applied Physics · 2009
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsAmerican Chemical Society Petroleum Research FundSouth Carolina EPSCoRClemson UniversityU.S. Department of Energy
KeywordsThermoelectric effectMaterials scienceElectrical resistivity and conductivitySeebeck coefficientThermal conductivityAnalytical Chemistry (journal)Hot pressingThermoelectric materialsFigure of meritCharge carrierCondensed matter physicsMetallurgyChemistryThermodynamicsOptoelectronicsComposite materialElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Mo 3 Sb 7 − x Te x is a high temperature thermoelectric material, reported to reach figure of merit (ZT)=0.8 at 1023 K. Various p-type samples of NiyMo3Sb7−xTex were prepared with y≤0.1 and 1.5≤x≤1.7 via high temperature reactions at 993 K. Adding transition metal atoms into the empty cube formed by Sb atoms significantly alters the band structure and thus the thermoelectric properties. Electronic band structure calculations indicate that adding Ni slightly increases the charge carrier concentration, while higher Te content causes a decrease. Thermoelectric properties were determined on pellets densified via hot pressing at 993 K. Seebeck as well as electrical and thermal conductivity measurements were performed up to 1023 K. The highest ZT value thus far was obtained from a sample of nominal composition Ni0.06Mo3Sb5.4Te1.6, which amounts to 0.93 at 1023 K.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.025
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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.

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

Citations23
Published2009
Admission routes2
Has abstractyes

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