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Record W2468673274 · doi:10.1002/pen.24382

Wrinkling in polymer film‐polymer substrate systems and a technique to minimize these surface distortions

2016· article· en· W2468673274 on OpenAlexafffund
Ganesh Balamurugan, Rohan N. Pukadyil, Michael R. Thompson, Kent E. Nielsen, Frank A. Brandys

Bibliographic record

VenuePolymer Engineering and Science · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsBP (Canada)McMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermoformingMaterials scienceComposite materialSubstrate (aquarium)PolymerPolymer substrateThermal expansionThermal

Abstract

fetched live from OpenAlex

Thermally induced wrinkling during thermoforming of a commercial multi‐layered polymer film/substrate laminate has been reported. The differential thermal expansion of component layers coupled with phase transition of the substrate with increasing temperature, determined the critical conditions for wrinkling with a specific wavelength and amplitude. An effective technique to minimize wrinkling by biaxially stretching the samples at high temperature before the forming operation, has been proposed. The samples were biaxially stretched by inflating the samples using a specially designed blowing unit retrofitted to a conventional vacuum thermoformer. This method involved heating, inflation and forming, together to provide stretch‐assisted thermoforming. During biaxial stretching the stored compressive stresses in a wrinkled sample were relieved before the forming step, producing a decorative part without losses in surface appearance. POLYM. ENG. SCI., 57:31–43, 2017. © 2016 Society of Plastics Engineers

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 score0.110
Threshold uncertainty score0.608

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 head0.008
GPT teacher head0.208
Teacher spread0.199 · 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

Citations3
Published2016
Admission routes2
Has abstractyes

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