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Record W2297625115 · doi:10.1002/mren.201500076

Modeling the Radical Batch Homopolymerization of Acrylamide in Aqueous Solution

2016· article· en· W2297625115 on OpenAlexaff
Calista Preusser, Anna Chovancová, Igor Lacı́k, Robin A. Hutchinson

Bibliographic record

VenueMacromolecular Reaction Engineering · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsQueen's University
FundersSlovenská Akadémia Vied
KeywordsMonomerRadicalAqueous solutionAcrylamideChemistryMolar massKineticsPolymerPolymer chemistryRadical polymerizationPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A kinetic model for the radical homopolymerization of acrylamide in aqueous solution is developed, incorporating propagation and termination rate coefficients as functions of monomer concentration and including the formation and reaction of midchain radicals based on the insights and measured rate coefficients from recent pulsed‐laser studies. The model successfully represents the batch conversion profiles measured using an in situ NMR technique between 40 and 70 °C with initial monomer concentrations of 5 to 40 wt%, as well as the associated polymer molar mass distributions. In particular, the model captures the decreased rate that occurs at lowered monomer concentrations as a result of the formation of less‐active midchain radicals by backbiting. Previous literature data are also well represented by the model. image

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.169
Teacher spread0.164 · 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 designSimulation or modeling
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

Citations25
Published2016
Admission routes1
Has abstractyes

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