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Electrodeposited Nanocrystalline Ni-Fe with Banded Structure

2012· article· en· W2070672227 on OpenAlexaff
Uta Klement, Mehrdad Shahabi-Navid, G.D. Hibbard

Bibliographic record

VenueMaterials science forum · 2012
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNanocrystalline materialMaterials scienceElectron backscatter diffractionGrain growthAnnealing (glass)MicrostructureCrystallographyTexture (cosmology)Grain sizeMetallurgyImpurityAlloyAbnormal grain growthNanotechnologyChemistry

Abstract

fetched live from OpenAlex

The microstructure of a Ni–18 wt.% Fe electrodeposits having a banded structure is described in detail. The aim is to investigate the influence of the banded structure on grain growth behaviour and texture and to elucidate if there are other mechanisms operative in the stabilization of nanocrystalline electrodeposits. Spectroscopy techniques have been used to characterize the variations in alloy/impurity concentration perpendicular to the growth direction. The influence of these chemical variations on the microstructural evolution has been monitored by in-situ annealing treatments in the TEM. Local texture of the annealed material has been determined by use of the electron backscatter diffraction (EBSD) technique. SEM and TEM investigations have shown that the banded structure is not related to phase changes and that grain growth is not affected by the banded structure, i.e. there is no preferred growth along bands. The first grown grains have <100>, <112> and <111> orientations with the growth direction and upon further grain growth a <111> fibre texture with respect to the growth direction of the electrodeposits is formed. The banded structure seems not to affect the general behaviour of nanocrystalline electrodeposits.

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 score0.003
Threshold uncertainty score0.005

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 head0.003
GPT teacher head0.184
Teacher spread0.182 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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