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Record W1979174951 · doi:10.1039/c0gc00326c

Cellulose nanocrystallites as an efficient support for nanoparticles of palladium: application for catalytichydrogenation and Heck coupling under mild conditions

2010· article· en· W1979174951 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

VenueGreen Chemistry · 2010
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIodobenzeneHeck reactionCatalysisCelluloseChemical engineeringMaterials scienceDispersityNanoparticlePalladiumPhenolNanocelluloseStackingStyreneColloidOrganic chemistryChemistryPolymer chemistryNanotechnologyPolymer

Abstract

fetched live from OpenAlex

We report herein the synthesis of a new hybrid material, PdNPs@CNCs consisting of monodisperse Pd nanoparticles (PdNPs) evenly deposited onto colloidal cellulose nanocrystallites (CNCs). This material proved an active catalyst for the hydrogenation reaction of phenol to cyclohexanone in water as a solvent, at room temperature, under 4 bar of dihydrogen. Moreover, the catalyst perfomed well in the Heck coupling of styrene and iodobenzene in a hydro-organic mixture. CNCs constitute a highly crystalline, ordered and yet accessible green material easily obtained from wood pulp. This work demonstrates the possibility of using colloidal CNCs as an efficient support for catalysis.

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 score0.015
Threshold uncertainty score0.495

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 head0.018
GPT teacher head0.305
Teacher spread0.288 · 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