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Record W2069324856 · doi:10.1039/c4dt01441c

Thermoelectric properties of higher manganese silicide/multi-walled carbon nanotube composites

2014· article· en· W2069324856 on OpenAlexafffund
Dao Y Nhi Truong, Holger Kleinke, Franck Gascoin

Bibliographic record

VenueDalton Transactions · 2014
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaRégion Normandie
KeywordsCarbon nanotubeThermoelectric effectSilicideMaterials scienceManganeseComposite materialNanotechnologyEngineering physicsMetallurgy

Abstract

fetched live from OpenAlex

Composites made of Higher Manganese Silicide (HMS)-based compound MnSi1.75Ge0.02 and multi-walled carbon nanotubes (MWCNTs) were prepared by an easy and effective method including mechanical milling under mild conditions and reactive spark plasma sintering. SEM compositional mappings show a homogeneous dispersion of MWCNTs in the HMS matrix. Electronic and thermal transport properties were measured from room temperature to 875 K. While power factors are virtually unchanged by the addition of MWCNTs, the lattice thermal conductivity is significantly reduced by about 30%. As a consequence, the maximum figure of merit for the composites with 1 wt% MWCNTs is improved by about 20% compared to the MWCNT free HMS-based sample.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.226
Teacher spread0.204 · 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

Citations35
Published2014
Admission routes2
Has abstractyes

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