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Record W2081111774 · doi:10.1021/ie061506e

Catalyst Solubility and Experimental Determination of Equilibrium Constants for Heterogeneous Atom Transfer Radical Polymerization

2007· article· en· W2081111774 on OpenAlexafffund
Santiago Faucher, Paul Okrutny, Shiping Zhu

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2007
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolubilityAtom-transfer radical-polymerizationCatalysisChemistryPolymerizationReaction rate constantLigand (biochemistry)MetalPolymer chemistryTolueneEquilibrium constantInorganic chemistryOrganic chemistryPolymerKinetics

Abstract

fetched live from OpenAlex

The solubilities of heterogeneous atom transfer radical polymerization (ATRP) catalysts are determined for the first time and used to calculate previously unquantified ATRP equilibrium constants ( K ATRP ). These new data are essential for understanding, modeling, and designing ATRP processes with low catalyst concentrations. K ATRP values for Cu I Br/1,1,4,7,10,10-hexamethyltriethylenetetramine (Cu I Br/HMTETA) and Cu I Br/ N, N, N ‘, N ‘, N ‘ ‘-pentamethyldiethylenetriamine (Cu I Br/PMDETA) are 8.66 × 10 -6 and 1.44 × 10 -6, respectively. The limited solubility of the Cu I Br/HMTETA catalyst explains why large reductions in metal salt concentration can be made without affecting polymerization rates. Catalyst solubility and polymerization rate increase with ligand concentration. In contrast, increasing the metal salt concentration in excess of the ligand's causes a drop in catalyst solubility. This unexpected observation is attributed to the formation of insoluble catalyst networks (gels). The solubility data point to differences in the ionic character of the catalyst complexes formed. The following solubility trend is observed at ATRP conditions (toluene, 90 °C): Cu I Br/PMDETA ≫ Cu II Br 2 /PMDETA > Cu II Br 2 /HMTETA > Cu I Br/HMTETA.

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 score0.006
Threshold uncertainty score0.775

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 head0.058
GPT teacher head0.331
Teacher spread0.273 · 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

Citations34
Published2007
Admission routes2
Has abstractyes

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