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Record W1495846857 · doi:10.4271/2004-01-1673

Alumina-Polymer E-Coatings With Increased Wear Resistance

2004· article· en· W1495846857 on OpenAlexaff
Michael N.C. Chen, Carmen Oprea, Tom Troczynski

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2004
Typearticle
Languageen
FieldEngineering
TopicElectrophoretic Deposition in Materials Science
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials sciencePolymerComposite materialWear resistance

Abstract

fetched live from OpenAlex

<div class="htmlview paragraph">Polymer E-coat has been a common method of protecting automotive body panels and many other accessories for outdoor use against corrosion. Typically, the polymer is composed of epoxy or acrylics in a water based suspension. This work focuses on increasing the coating properties such as scratch and wear resistance, with the addition of fine dispersed ceramic into the suspension, creating a polymer matrix with reinforced ceramic particles as finish product. Also, there has been no alteration of the processing technique, which signifies a good method of improving the mechanical properties of this auto body coat. The coating chemistry and microstructure have been studied. The essential mechanical properties of the coatings have been evaluated. It is shown that by introducing the ceramic reinforcement phase, the scratch and wear resistance is increased significantly without influencing bonding properties.</div>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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.

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

Citations0
Published2004
Admission routes1
Has abstractyes

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