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Record W2165079093 · doi:10.1002/masy.200651117

Estimation of Free Radical Polymerization Rate Coefficients Using Computational Chemistry

2006· article· en· W2165079093 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.

Bibliographic record

VenueMacromolecular Symposia · 2006
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsHutchinson (Canada)Queen's University
FundersDivision of Materials Research
KeywordsPolymerizationRadical polymerizationCopolymerMonomerPolymer chemistryThermodynamicsBulk polymerizationStyreneMethacrylateChemistryMaterials scienceOrganic chemistryPolymerPhysics

Abstract

fetched live from OpenAlex

Abstract This study explores the application of computational chemistry to estimate free radical polymerization rate coefficients. The Evans‐Polanyi relationship is combined with computed heats of polymerization to estimate copolymerization reactivity ratios for many vinyl monomer pairs, focusing on acrylates, methacrylates and styrene, with accuracy assessed by comparison to experimental values. The effect of different optimization approaches on the values of thermodynamic properties is explored, and it is concluded that a combination of conventional optimization and relaxed potential energy scans was most effective at identifying global minima. The difference between thermodynamic properties calculated using the harmonic oscillator treatment and a hindered rotor model is evaluated for methyl methacrylate 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 score0.237
Threshold uncertainty score0.721

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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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