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Record W4386928807 · doi:10.1016/j.jmrt.2023.09.167

Obtaining and characterisation of thermoelectric Mg2Si compound via wet and dry mechanical alloying and spark plasma sintering

2023· article· en· W4386928807 on OpenAlexfundno aff
V. CEBOTARI, Florin Popa, Traian Florin Marinca, B.V. Neamţu, Niculina Sechel, Magdalena Galatanu, Andrei Galatanu, I. Chicinaş

Bibliographic record

VenueJournal of Materials Research and Technology · 2023
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsnot available
FundersColegiul Consultativ pentru Cercetare-Dezvoltare şi InovareMinistry of Education and Research, RomaniaUniversitatea Tehnică din Cluj-NapocaUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiOntario Ministry of Research, Innovation and Science
KeywordsSpark plasma sinteringMaterials scienceScanning electron microscopeDifferential scanning calorimetryThermoelectric effectParticle sizeSeebeck coefficientParticle-size distributionAnalytical Chemistry (journal)Particle (ecology)Thermal conductivityMetallurgyComposite materialChemical engineeringSinteringThermodynamicsChromatography

Abstract

fetched live from OpenAlex

Mg2Si thermoelectric compound was obtained by dry and wet (isohexane and benzene) mechanical alloying route. The Mg2Si compound was characterised by X-ray diffraction, scanning electron microscopy (SEM), differential scanning calorimetry (DSC), laser particle size analysis and thermoelectric measurements. After 14 h of milling, the complete reaction of the elements is achieved by both routes. The powders particle size distribution obtained after 14 hours of dry or wet milling (using benzene) reveals a bimodal curve. The wet milling moves the particle size distribution towards smaller particle sizes. The SEM analysis confirms the results of particles size analysis. DSC analyses performed for samples milled up to 14 hours present stress relief and recrystallisation thermal events. For the benzene wet-milled sample, the DSC curve shows an additional thermal event at 350 °C, associated with benzene removal. Thermoelectric properties were determined on spark plasma sintered compacts. The milling process with benzene leads to a higher value of Seebeck coefficient (≈580 μV/K). The electrical conductivity is low at room temperature and increases exponentially with temperature.

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)0.002
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 score0.017
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.039
GPT teacher head0.323
Teacher spread0.284 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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