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Thermal Conductivity and Electrical Resistivity in Polycrystalline and Nanocrystalline Nickel

2011· article· en· W2026963538 on OpenAlexafffund
Shihao Wang, I. Brooks, J.L. McCrea, G. Palumbo, G. Cingara, U. Erb

Bibliographic record

VenueAdvanced materials research · 2011
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanocrystalline materialElectrical resistivity and conductivityMaterials scienceCrystalliteGrain sizeNickelGrain boundaryMetallurgyThermal conductivityComposite materialMicrostructureNanotechnologyElectrical engineering

Abstract

fetched live from OpenAlex

The grain-size dependences of thermal conductivity and electrical resistivity of polycrystalline and nanocrystalline nickel were measured by the flash method and four-point probe method, respectively. Nanocrystalline nickel (grain size: 28 nm) was made by the pulsed-current electrodeposition process, while polycrystalline nickel (grain size: 57 μm) was the same material in fully annealed condition. Noticeable differences in thermal conductivity and electrical resistivity were observed for both materials. These results can be explained on the basis of the rapid increase in the intercrystalline grain boundary and triple junction volume fractions at very small grain sizes. The relationship between thermal conductivity and electrical resistivity of nanocrystalline nickel follows the classic Wiedemann-Franz law.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.087
GPT teacher head0.329
Teacher spread0.242 · 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

Citations7
Published2011
Admission routes2
Has abstractyes

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