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Record W2909038806 · doi:10.3139/146.111735

Kinetics of intermetallic compound layers during initial period of reaction between mild steel and molten aluminum

2019· article· en· W2909038806 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.

Bibliographic record

VenueInternational Journal of Materials Research (formerly Zeitschrift fuer Metallkunde) · 2019
Typearticle
Languageen
FieldEngineering
TopicIntermetallics and Advanced Alloy Properties
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIntermetallicMaterials scienceDissolutionMicrostructureAluminiumActivation energyScanning electron microscopeKineticsAtmospheric temperature rangeDecompositionMetallurgyAnalytical Chemistry (journal)DiffractionThermodynamicsComposite materialPhysical chemistryChemistry

Abstract

fetched live from OpenAlex

Abstract Hot dip aluminizing of mild steel at different temperatures was conducted to reveal the influence of reaction temperature and time on interfacial intermetallic compounds (IMCs). Scanning electron microscopy, energy dispersive X-ray spectrometry and X-ray diffraction were employed to investigate the interfacial microstructures. The IMCs of the dipping interface consisted of a thick layer of η-Fe 2 Al 5 between 4.2–132.2 μm next to the steel and a thin layer of θ-Fe 4 Al 13 between 0–5.5 μm close to the aluminum. With increasing dipping temperature and time, the total thickness of IMCs (Fe 2 Al 5 plus Fe 4 Al 13 ) increased. Specifically, the growth of the Fe 2 Al 5 layer can be described by parabolic rate laws. An activation energy of 93 kJ mol −1 was obtained, combining both the results from the present work and previous studies in the temperature range of 675–900°C. The change in Fe 4 Al 13 thickness is not significant compared with the Fe 2 Al 5 . However, the decrease in IMC thickness of the Fe 4 Al 13 with dipping temperature was observed for the first time and had never been reported before. Moreover, it can be clearly observed that the thickness of the Fe 4 Al 13 decreased with dipping time based on the linear fitting results by excluding the result of the initial 1 s. A possible mechanism is that interfacial dynamics and thermodynamics work for the dissolution and decomposition of the Fe 4 Al 13 layer. Higher temperature accelerates the dissolution of the θ layer.

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)0.001
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 score0.012
Threshold uncertainty score0.874

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.040
GPT teacher head0.323
Teacher spread0.282 · 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