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Record W4406936049 · doi:10.71330/thenucleus.2010.881

NANOCOMPOSITE SURFACES – A REVIEW

2010· review· en· W4406936049 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Nucleus · 2010
Typereview
Languageen
FieldEngineering
TopicLaser-Ablation Synthesis of Nanoparticles
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsNanocompositeMaterials scienceComposite materialNanotechnology

Abstract

fetched live from OpenAlex

The development of nanocomposite surfaces offers significant improvements in mechanical properties over conventional microstructured surfaces. However, to develop nanostructured surfaces for abrasive wear resistant applications still remains a challenge. This paper gives an overview of some of the more successful spraying techniques such as High Velocity Oxy-Fuel (HVOF) spraying that have been used to deposit thick nanostructured WCCo based coatings. The retention of the nanostructure developed in the feedstock powders through control of spraying parameters has some limited success in preventing decarburization of the WC nano-sized dispersion in the Co matrix. The use of a novel duplex Co-coated powder has the effect of eliminating decarburization and this is reflected in a noticeable increase in mechanical and wear resistant properties of the final coating. Cold gas dynamic spraying techniques have also been used to control the final composition and grain structure of WC-Co based coatings and the corresponding properties changes are compared and discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.033
GPT teacher head0.281
Teacher spread0.248 · 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