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Record W1556274093 · doi:10.1063/1.1499521

Influence of Se on the electron mobility in extruded Bi2(Te1−xSex)3 (x⩽0.125) thermoelectric alloys

2002· article· en· W1556274093 on OpenAlexafffund
D. Vasilevskiy, A. Sami, J.-M. Simard, R. A. Masut

Bibliographic record

VenueJournal of Applied Physics · 2002
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaPolytechnique Montréal
KeywordsMaterials scienceThermoelectric effectSeebeck coefficientAnnealing (glass)Electron mobilityCondensed matter physicsExtrusionScatteringCharge carrierAtmospheric temperature rangeCrystalliteCarrier scatteringElectronegativityPhonon scatteringThermoelectric materialsAlloyPhononElectrical resistivity and conductivityAnalytical Chemistry (journal)ChemistryMetallurgyThermodynamicsComposite materialThermal conductivityOptoelectronicsOptics

Abstract

fetched live from OpenAlex

We present the electrical transport properties of thermoelectric n-type Bi2(Te1−xSex)3 (x⩽0.125) polycrystalline alloys obtained by mechanical alloying and extrusion. It was determined that the charge carrier mobility decreases in the temperature range 90–300 K as the content (x) of Bi2Se3 is increased. The observed decrease is larger than what could be predicted by the introduction of an alloy scattering mechanism due to the electronegativity difference between Se and Te atoms. It can be explained by the introduction of additional defects induced by the Se incorporation, whose concentration is reduced by thermal annealing following extrusion. In the extrinsic regime, the observed temperature dependence of the mobility [μ=μ0(T/T0)r] of as extruded alloys apparently indicates that charge carrier scattering is mostly limited by acoustic phonons (temperature coefficient r near −1.5). Annealing after extrusion changes the temperature coefficient to values near −1.7 which is closer to what has been reported for pure crystalline Bi2Te3.

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)0.000
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 score0.034
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
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; 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

Citations29
Published2002
Admission routes2
Has abstractyes

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