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Record W4376881300 · doi:10.31399/asm.cp.itsc2023p0280

Effect of Carbon Fiber Orientation when Cold Spraying Metallic Powders onto Carbon Fiber Reinforced Polymers

2023· article· en· W4376881300 on OpenAlex
Andre C. Liberati, Payank Patel, Amit Roy, Phuong Vo, Chunzhou Pan, Christian Moreau, Richard R. Chromik, Stephen Yue, Pantcho Stoyanov

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

VenueThermal spray · 2023
Typearticle
Languageen
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsNational Research Council CanadaMcGill UniversityConcordia University
FundersNational Research Council Canada
KeywordsMaterials sciencePeekComposite materialPolyether ether ketoneScanning electron microscopeThermoplasticSubstrate (aquarium)CoatingPolymerFiberComposite numberAdhesion

Abstract

fetched live from OpenAlex

Abstract A previous study on the pull-off testing of metallized carbon fiber reinforced polymers (CFRPs) via cold spray showed that better adhesion strengths could be obtained when features such as carbon fibers or surfacing elements were present, by providing potential mechanical interlocking features. In this work, the effect of the fiber orientation on the deposition and bonding of the metallic coating to the thermoplastic composite substrate is explored. Pure Sn powder was cold sprayed onto two thermoplastic Polyether-Ether- Ketone (PEEK) CFRP substrates, containing carbon fibers with different orientations: one had fibers in the plane of the substrate (uni-directional tape), while the other had fibers mostly perpendicular to the substrate (ZRT film). Characterization of the coatings was performed via scanning electron microscopy (SEM) and confocal microscopy, and some aspects of mechanical testing (namely wear and scratch testing) were carried out to assess the effect of the substrate on the properties of the coatings.

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 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 score0.039
Threshold uncertainty score0.726

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 head0.006
GPT teacher head0.221
Teacher spread0.215 · 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