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Record W4220932890 · doi:10.1002/cctc.202101621

From Deep Eutectic Solvents to Nitrogen‐rich Ordered Mesoporous Carbons: A Powerful Host for the Immobilization of Palladium Nanoparticles in the Aerobic Oxidation of Alcohols

2022· article· en· W4220932890 on OpenAlexaff
Seyedeh Zahra Alizadeh, Babak Karimi, Hojatollah Vali

Bibliographic record

VenueChemCatChem · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsCatalysisMesoporous materialChemistryPalladiumDeep eutectic solventInorganic chemistryAdsorptionCholine chlorideEutectic systemNanoparticleCarbonizationActivated carbonAlcohol oxidationOrganic chemistryMaterials scienceAlloyNanotechnology

Abstract

fetched live from OpenAlex

Abstract The preparation of a nitrogen‐rich ordered mesoporous carbon (DNOMC) with three‐dimensional cubic structure was established via carbonization of a green, inexpensive and safe deep eutectic solvent consisting of choline chloride salt and D‐glucose in the presence of KIT‐6 template for the first time. The materials were characterized by TEM, N 2 adsorption–desorption analysis, XPS, TGA, CHN, and FT‐IR. The DNOMC was shown to be a powerful support for the immobilization of palladium nanoparticles. The Pd@DNOMC catalyst exhibited high activity in the selective aerobic oxidation of various activated and non‐activated primary and secondary benzylic as well as linear and cyclic aliphatic alcohols to the corresponding carboxylic acids and ketones in pure water under molecular oxygen. The catalyst system could successfully be reused at least ten times without any significant decrease in either activity or selectivity. It is worth noting that, the hot filtration strongly showed that the catalyst works in a boomerang‐type catalyst pathway.

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)0.000
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 score0.001
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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