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Record W2950818180 · doi:10.1021/cm0708517

Thermoelectric Properties of Re<sub>3</sub>Ge<sub>0.6</sub>As<sub>6.4</sub> and Re<sub>3</sub>GeAs<sub>6</sub> in Comparison to Mo<sub>3</sub>Sb<sub>5.4</sub>Te<sub>1.6</sub>

2007· article· en· W2950818180 on OpenAlexaff
Navid Soheilnia, Hong Xu, Huqin Zhang, Terry M. Tritt, I. P. Swainson, Holger Kleinke

Bibliographic record

VenueChemistry of Materials · 2007
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsThermoelectric effectIsostructuralThermoelectric materialsMaterials scienceSeebeck coefficientDopingElectrical resistivity and conductivityFigure of meritSemiconductorThermal conductivityCrystal structureCondensed matter physicsOptoelectronicsCrystallographyThermodynamicsChemistryComposite materialElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Heavily doped narrow gap semiconductors with complex crystal structures are prime candidates for thermoelectric materials. The arsenides Re 3 (Ge,As) 7 are new examples with promising thermoelectric properties, comparable with the isostructural Mo 3 Sb 5.4 Te 1.6, a competitive high-temperature material. Various doping levels may be achieved by using different Ge/As ratios. Re 3 (Ge,As) 7 was prepared by heating the elements in the desired ratios in evacuated silica tubes between 600 and 800 °C. Re 3 GeAs 6 crystallizes in the cubic Ir 3 Ge 7 type, space group Im 3̄ m, with a = 8.73202(8) Å. It exhibits high Seebeck coefficient, high electrical conductivity, and reasonably low thermal conductivity. Moreover, the thermoelectric figure-of-merit ZT = TS 2 σ/κ increases rapidly with increasing temperature, as desired for high-temperature thermoelectrics.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
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 score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0060.006
Meta-epidemiology (broad)0.0100.002
Bibliometrics0.0020.005
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0050.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.243
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

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

Citations24
Published2007
Admission routes1
Has abstractyes

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