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Record W4320522706 · doi:10.31399/asm.cp.itsc2012p0243

Cold Spray Forming Inconel 718

2012· article· en· W4320522706 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

VenueThermal spray · 2012
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsMcGill UniversityNational Research Council Canada
Fundersnot available
KeywordsInconelGas dynamic cold sprayMaterials scienceNozzleCoatingMetallurgySpray nozzlePorosityDuctility (Earth science)Composite materialExtrusionSinteringNitrogenMicrostructureHeliumUltimate tensile strengthAlloyCreep

Abstract

fetched live from OpenAlex

Abstract In this investigation, Inconel 718, a material known to cause nozzle clogging upon cold spraying, was cold spray formed to 6 mm-thick using the Plasma Giken cold spray system PCS- 1000. This was made possible due to the novel non-clogging nozzle material combined with a nozzle water cooling system. Coatings were as-spray formed using both nitrogen and helium as the propelling gasses. The resulting microstructures as well as the corresponding mechanical properties were studied. In addition, the effect of post-heat treatments was also investigated. It was found that for a given propelling gas used, the coating porosity level remained relatively similar (about 2.4% for nitrogen and 3.6% for helium) regardless of the coating treatment (as-sprayed or heat treated). Visual inspection from SEM micrographs showed a higher fraction of inter-particle metallurgical bonds for nitrogen gas sprayed coatings heat treated at 1250°C for 1 hour due to some sintering effect. This significantly affected its tensile properties with an average resulting ductility of 24.7%.

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)0.000
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 score0.057
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

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)0.0000.001

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 head0.221
Teacher spread0.209 · 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