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Record W2914594695 · doi:10.5151/1516-392x-25018

INVESTIGATIONS ON THE ROLE OF COPPER IN CAUSING AND NICKEL IN PREVENTING THE “HOT SHORTNESS” IN STEELS

2014· article· en· W2914594695 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

VenueABM Proceedings · 2014
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsMcGill University
Fundersnot available
KeywordsNickelCopperMetallurgyMaterials science

Abstract

fetched live from OpenAlex

An extensive investigation into the role of low copper contents on the hot ductility of C-Mn-Al steels has been carried out in order to better understanding the problem of "hot shortness". Previous work has suggested that this problem results from the build up of Cu that occurs at the surface of the steel as a consequence of the preferential oxidation of iron. This causes the formation of a Cu-rich film of low melting point. A nickel addition has been reported as a solution to the problem, since it increases the solubility of copper in the austenite. After hot tensile testing to failure, samples of Cucontaining steels have been examined using optical, scanning and transmission electron microscopes. Recently published results indicate that copper, in addition to precipitating out as CuS, also segregates to MnS inclusions forming a shell around them. This does not seem to impair the hot ductility under an inert atmosphere, but may have serious consequences under an oxidising environment and lead to "hot shortness". The influence of nickel in improving the hot ductility seems to be due to it forming a higher melting point alloy with the segregated copper. Data from this incomplete work also suggests that Ni reduces the precipitation of CuS particles. Current investigation carried out using confocal microscopy still to be completed will improve the understanding of the role of copper and nickel on the problem of "hot shortness".

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 score0.197
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.012
GPT teacher head0.205
Teacher spread0.194 · 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