MétaCan
Menu
Back to cohort

Thermoelectric Material Design in Pseudo Binary Systems of Mg<sub>2</sub>Si – Mg<sub>2</sub>Ge – Mg<sub>2</sub>Sn on the Powder Metallurgy Route

2007· article· en· W2070000347 on OpenAlexaff
Tatsuhiko Aizawa, Ren Bo Song, Atsushi Yamamoto

Bibliographic record

VenueMaterials science forum · 2007
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThermoelectric effectMaterials scienceThermoelectric materialsDopingSolid solutionTinThermoelectric generatorMicrostructureGermaniumElectrical resistivity and conductivityChemical compositionMetallurgyOptoelectronicsThermodynamicsElectrical engineeringPhysicsSilicon

Abstract

fetched live from OpenAlex

Fundamental studies on the thermoelectricity have been mainly done in the pseudo binary systems of Mg2Si – Mg2Ge – Mg2Sn. In recent years, their thermoelectricity is revisited because of light-weight, low initial const and short turning back time in addition to high potential in figureof- merit for ZT approaching to unity or more. Conventional melting and solidification, or, normal PM routes fail in precise, wide-range control of chemical composition and microstructure control. New PM route via bulk mechanical alloying is developed to fabricate the solid solution semiconductive materials with Mg2Si1-xGex and Mg2Si1-ySny for 0 < x, y < 1 and to investigate their thermoelectric materials. Since Mg2Si is n-type and both Mg2Ge and Mg2Sn are p-type, pntransition takes place at the specified range of germanium content, x, and tin content, y. Through optimization of chemical composition, solid-solution type thermoelectric semi-conductive materials are designed both for n- and p-type materials. In addition, appropriate doping condition can be searched in the specified range of x and y.

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)0.023
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
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 score0.025
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.002
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0030.007
Science and technology studies0.0030.004
Scholarly communication0.0040.005
Open science0.0090.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueMaterials science forumSame topicAdvanced Thermoelectric Materials and DevicesFrench-language works237,207