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Optimization of thermoelectric properties of n-type Mn- and Te-doped Mg3Sb2-Bi phases

2025· article· en· W4411225251 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSolid State Sciences · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsNatural Resources CanadaMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDopingThermoelectric effectMaterials scienceThermoelectric materialsCondensed matter physicsChemistryPhysicsThermodynamics

Abstract

fetched live from OpenAlex

This study explores the effects of Mg and Bi amounts, ball milling duration, and sintering conditions on the purity and thermoelectric properties of the Mn- and Te-doped Mg 3 Sb 2- x Bi x phases (Mg 2.97+ y Mn 0.03 Bi x Sb 1.99- x Te 0.01 ). We found that excess Mg is necessary to achieve phase pure samples, but too much Mg forms impurities that decrease thermoelectric efficiency. Increasing Bi content leads to lower phase stability and decomposition. There is also an optimal ball milling time, beyond which decomposition of the material occurs. The highest figure of merit, zT, of 1.44 was achieved for the Mg 3.27 Mn 0.03 Bi 1.30 Sb 0.69 Te 0.01 sample at 623K, which is comparable to the performance of Bi 2 Te 3 . Our findings suggest that Mg 3 Sb 2- x Bi x phases are promising low-cost and environmentally friendly thermoelectric materials mid-range temperature applications.

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.

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 score0.004
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.284
Teacher spread0.265 · 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