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Record W4301936661 · doi:10.31399/asm.cp.itsc2004p1034

Abrasion Behavior of Nanostructured and Conventional Titania Coatings Thermally Sprayed via APS, VPS and HVOF

2004· article· en· W4301936661 on OpenAlexaff
R.S. Lima, L. Leblanc, B.R. Marple

Bibliographic record

VenueThermal spray · 2004
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsPyrogenesis (Canada)
Fundersnot available
KeywordsThermal sprayingMaterials scienceAbrasion (mechanical)MicrostructureCoatingPorosityComposite materialParticle (ecology)Metallurgy

Abstract

fetched live from OpenAlex

Abstract Nanostructured and conventional titania feedstocks were thermally sprayed using APS, VPS and HVOF techniques to study the effects of processing, microstructure and properties on the abrasion behavior. The in-flight characteristics (temperature and velocity) of the APS and HVOF-sprayed particles were also investigated. For the nanostructured coatings, a process map was developed relating the in-flight particle characteristics during coating deposition to the abrasion resistance. This map showed that the particle velocity and particle temperature had an important influence on the volume loss in abrasion tests. Coatings were characterized using SEM to investigate the microstructural features, image analysis to measure coating porosity and Vickers indentation to determine hardness. The abrasion behavior of the coatings was evaluated using the ASTM standard dry sand/rubber wheel test. The abrasion results indicated that the VPS and HVOF-sprayed nanostructured titania coatings exhibited the highest abrasion resistance among the 14 coatings studied.

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.

How this classification was reachedexpand

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 score0.290
Threshold uncertainty score0.852

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)0.0000.000

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 head0.005
GPT teacher head0.205
Teacher spread0.200 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2004
Admission routes1
Has abstractyes

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