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Record W2076486037 · doi:10.1002/polb.23114

Dynamic mechanical properties and swelling of UV‐photopolymerized anionic hydrogels

2012· article· en· W2076486037 on OpenAlexaff
Joseph Ryan Saunders, Walied A. Moussa

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhotopolymerSelf-healing hydrogelsSwellingMaterials scienceMethacrylateDynamic mechanical analysisPotassium hydroxideScanning electron microscopePolymer chemistryComposite materialChemical engineeringElastic modulusPolymerizationPolymer

Abstract

fetched live from OpenAlex

Abstract The tensile dynamic mechanical properties and weight degree of swelling for anionic 2‐hydroxyethyl methacrylate‐ co ‐acrylic acid hydrogels were observed. Fabrication parameters examined were UV‐photopolymerization exposure time, UV‐photopolymerization intensity, and weight percentage crosslinker. The environmental conditions tested were electrolyte compositions of 0.5 and 0.05 M potassium hydroxide under applied frequencies of 0.1, 1, or 10 Hz. The overall maximum and minimum storage modulus was 1.83 ± 0.18 MPa and 68.5 ± 7.2 kPa, respectively, loss modulus was 432 ± 63 and 7.67 ± 3.22 kPa, respectively, and weight degree of swelling was 14.27 ± 1.27 and 1.95 ± 0.33, respectively. The morphology of fabricated hydrogels was examined using scanning electron microscopy showing a range of porous structures over the fabrication and environmental conditions examined, accounting for the variation in mechanical properties. The properties examined are of interest to researchers fabricating, designing, or modeling active hydrogel‐based microfluidic components. © 2012 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2012

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 score0.018
Threshold uncertainty score0.749

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 communication0.0000.001
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 head0.024
GPT teacher head0.238
Teacher spread0.214 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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