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Record W3193719174 · doi:10.31399/asm.cp.itsc2000p0895

Thermal Spray Processing of WC-Co Nanomaterials

2000· article· en· W3193719174 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 · 2000
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceCermetThermal sprayingIndentation hardnessMicrostructurePorosityMetallurgyPhase (matter)Composite materialCoatingCeramic

Abstract

fetched live from OpenAlex

Abstract WC-Co based cermets are extensively used in wear applications due to their hardness and toughness. Recent work has demonstrated the potential for using nanoscale constituents to improve the wear properties of these materials. In the present study, two WC-Co powders containing a nanosized WC phase were used to produce coatings by HVOF thermal spraying. These powders had similar properties except for the volume percent binder present: WC-8C0 and WC-12Co. The thermal spraying conditions were varied in order to identify their effect on the microstructure, properties and phase composition of the sprayed coatings. The as-sprayed coatings possess porosity values ranging between 1% and 2% and microhardness values (HV100) from 1150 to 1550, which are quite similar to values obtained for conventionally sized WC-based coatings. For all the coatings, phase analysis indicated significant degradation of the WC phase to produce W2C, W, CO3W3C and Co6W3C. For some spray conditions, even WO3 phase was found in the coatings. The JP-5000 HVOF system produces coatings with lower porosity, similar microhardness values and, more importantly, with lower WC degradation than the coatings produced with the DJ-2700.

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 categoriesInsufficient payload (model declined to judge)
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 score0.025
Threshold uncertainty score0.997

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)0.0040.000

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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