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Record W2038522060 · doi:10.1039/c3ta13106h

A conveniently synthesized polyethylene gel encapsulating palladium nanoparticles as a reusable high-performance catalyst for Heck and Suzuki coupling reactions

2013· article· en· W2038522060 on OpenAlexafffund
Pingwei Liu, Zhongming Dong, Zhibin Ye, Wenjun Wang, Bo‐Geng Li

Bibliographic record

VenueJournal of Materials Chemistry A · 2013
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsLaurentian University
FundersOntario Ministry of Research and Innovation
KeywordsIodobenzeneHeck reactionArylPalladiumCatalysisSuzuki reactionPolymer chemistryLeaching (pedology)SolventChemistryPolymerizationMaterials scienceOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

The synthesis of a polyethylene (PE) gel containing self-incarcerated palladium(0) nanoparticles is described. The PE gel matrix without any special functionality was synthesized by one-pot chain walking copolymerization of ethylene and 1,6-hexanediol diacrylate facilitated by a Pd–diimine complex (1). The Pd(II) species from 1 were immobilized in situ onto the gel matrix and further reduced to Pd(0) nanoparticles as a result of catalyst 1 deactivation during polymerization and methanol (a reducer) washing in the polymer purification process. The resulting Pd-containing PE gel (2) is shown to be a high-performance and facilely reusable heterogeneous catalyst for the Heck and Suzuki coupling reactions of iodobenzene or aryl bromides. An average TOF of 460 h−1 was achieved with an average 0.57 ppm Pd leaching in each cycle of the Heck reaction of iodobenzene when the PE gel 2 was recycled 10 times. A maximum TOF of 3.33 × 104 h−1 was reached and less than 0.64 ppm of Pd was leached in the Suzuki reactions of aryl bromides with water as solvent.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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.

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

Citations31
Published2013
Admission routes2
Has abstractyes

Explore more

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