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Record W4417368981 · doi:10.1002/pol.20251099

Who Lives in a Tin Can Under the (Ultrasonic) Sea: Sponges Made From Perfluoropyridine‐Derived Thiol‐Ene Polymerizations

2025· article· en· W4417368981 on OpenAlexafffund
Jason Pulfer, Miriam Aldom, Maxime Colpaert, Andrea R. Kelley, Tim Storr, Chadron M. Friesen

Bibliographic record

VenueJournal of Polymer Science · 2025
Typearticle
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsTrinity Western UniversitySimon Fraser UniversityWestern University
FundersU.S. Air Force AcademyNatural Sciences and Engineering Research Council of CanadaU.S. Air Force
KeywordsPrepolymerYield (engineering)Thermal stabilityRaw materialPolymerizationTinElastomerEther

Abstract

fetched live from OpenAlex

ABSTRACT Substitution of perfluoropyridine (PFP) in the 4‐position through an S N Ar reaction is facile through mechanochemical methods, with yields in excess of 99% and short reaction times on a multigram scale. Glycol materials can be end‐capped with PFP to create bis‐PFP ethers, which are capable of further activation in the 2‐ and 6‐positions by sonochemical means. A bis‐PFP ether was substituted sonochemically with eugenol in the 2‐ and 6‐positions to produce a prepolymer utilizing a bio‐based feedstock as a polymerizable motif; however, it was ultimately found to perform identically to a traditional thermal reaction. The resulting material was polymerized with a commercially available dithiol to yield crosslinked, insoluble, sponge‐like elastomers. The sponges display similar thermal stability ( T onset = 311°C–355°C), but highly variant glass transition temperatures ( T g = −35°C to 8°C), indicating that this is a viable methodology to create elastomers with tunable T g 's dependent on the nature of the central linker in the 4‐position.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.216
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes2
Has abstractyes

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