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Record W4400285776 · doi:10.1002/aic.18490

Accounting for spatial variations during photopolymerization of 1,6‐hexane‐diol diacrylate in the presence of oxygen

2024· article· en· W4400285776 on OpenAlex

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

VenueAIChE Journal · 2024
Typearticle
Languageen
FieldChemistry
TopicPhotopolymerization techniques and applications
Canadian institutionsQueen's University
FundersElectronic Components and Systems for European LeadershipMitacsKey Digital Technologies Joint Undertaking
KeywordsPhotopolymerDiolHexaneOxygenChemistryMaterials scienceOrganic chemistryPolymerPolymerization

Abstract

fetched live from OpenAlex

Abstract A dynamic model is proposed for photopolymerization of 1,6‐hexane‐diol diacrylate (HDDA) with bifunctional initiator bis‐acylphosphine oxide (BAPO) in the presence of oxygen. This partial‐differential‐equation model predicts time and spatially varying vinyl‐group conversion as well as concentrations of monomer, initiator, oxygen, and seven types of radicals. Experiments to obtain diffusivities of oxygen, BAPO and HDDA are reported. Oxygen‐related parameters are estimated using real‐time Fourier‐transform infrared (FTIR) conversion data. FTIR experiments were conducted using a range of film thicknesses (), BAPO levels () and light intensities (). The model predicts qualitative trends. Conversion predictions for runs with high intensities () and high BAPO () are accurate with a root‐mean‐squared error (RMSE) of 0.04. Larger RMSE (0.13) for runs with lower intensities and BAPO indicates that improved parameter estimates are required. Parameter estimates will be updated in future using a model that accounts for shrinkage during polymerization.

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 score0.129
Threshold uncertainty score0.258

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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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