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Wear Behaviour of HVOF Sprayed WC-Cobalt Coatings

2011· article· en· W1967790823 on OpenAlex
Abdul Mateen, Fazal Ahmad Khalid, Tahir I. Khan, Gobinda C. Saha

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

VenueAdvanced materials research · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMaterials scienceTribologyTungsten carbideCoatingMicrocrystallineThermal sprayingNanocrystalline materialToughnessMetallurgyCobaltComposite materialWear resistanceAbrasiveCarbideNanotechnology

Abstract

fetched live from OpenAlex

Tungsten carbide cobalt coating has been extensively used for cutting and mining tools, aerospace, automotive and other wear resistance applications. These coatings not only have superior mechanical properties like high hardness, toughness and compressive strength but have also excellent controllable tribological properties. In this paper a comparison of wear properties and structural phases has been presented to consider for tribological applications. It is found that nanocrystalline duplex coatings have shown much superior properties as compared to the microcrystalline coatings. Evidence of clusters of WC particles was found in microcrystalline coating as compared to homogeneous dense coating structure observed in the nanocrystalline coating. These results are discussed to assess their suitability for super hard wear resistance applications.

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 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 score0.012
Threshold uncertainty score1.000

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)0.0010.000

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 head0.054
GPT teacher head0.315
Teacher spread0.261 · 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