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Record W3171712863 · doi:10.31399/asm.cp.itsc2021p0611

Hybrid Metallic Coatings on Polymer-Based Composites

2021· article· en· W3171712863 on OpenAlexaff
Panteha Fallah, Stephen Yue, André McDonald

Bibliographic record

VenueThermal spray · 2021
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsUniversity of AlbertaMcGill University
Fundersnot available
KeywordsMaterials scienceGas dynamic cold sprayElectroplatingComposite materialPolymerCarbon fiber reinforced polymerSubstrate (aquarium)Deposition (geology)MetalParticle (ecology)Polymer substrateMetallurgyParticle sizeLayer (electronics)CoatingComposite numberChemical engineering

Abstract

fetched live from OpenAlex

Abstract A previous study showed that Cu can be cold sprayed onto carbon fiber-reinforced polymers (CFRPs) if a Cu interlayer is deposited prior to low-pressure cold spraying. In this present study, Cu was cold sprayed onto CFRP substrates that were coated with either Sn (cold spray) or Ni electroplating. Two layers of Cu powder were also cold sprayed onto a Cu-plated CFRP substrate to investigate the effect of a second particle layer on impacting particles. Test results showed that the relative hardness between the particle and substrate has a major effect on deformability, impact mode, and deposition efficiency (DE), which explains why Cu could not be cold sprayed onto Sn or Ni interlayers and why the deposition efficiency of Cu-on-Cu substrates is lower than that of one pass spraying. In summary, the results suggest that Cu can be successfully cold sprayed at low pressures onto electroplated Cu due to their similarity in hardness.

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 score0.005
Threshold uncertainty score0.834

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)0.0010.000

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 head0.011
GPT teacher head0.219
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

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

Citations1
Published2021
Admission routes1
Has abstractyes

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