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Record W2766270987 · doi:10.1088/1361-6528/aa95a2

Cellulose nanocrystal-derived hollow mesoporous carbon spheres and their application as a metal-free catalyst

2017· article· en· W2766270987 on OpenAlexafffund
Lida Hadidi, Ahmed Mahmoud, Tapas K. Purkait, Mark T. McDermott, Jonathan G. C. Veinot

Bibliographic record

VenueNanotechnology · 2017
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceSodium borohydrideCatalysisMesoporous materialCarbon fibersNanocrystalCelluloseChemical engineeringNanoparticleAmorphous carbonSPHERESMetalMesoporous silicaAmorphous solidNanotechnologyComposite materialComposite numberOrganic chemistryChemistryMetallurgy

Abstract

fetched live from OpenAlex

Abstract In this contribution, we demonstrate the fabrication of hollow mesoporous carbon spheres (HCSs) derived from cellulose nanocrystals (CNCs). The HCSs were prepared by templating CNCs onto sacrificial silica spheres followed by heat treatment. Mesoporous carbon spheres result from the removal of the silica spheres by etching. The walls of the HCSs are approximately 4 nm thick and are composed of amorphous and graphitic carbon. The catalytic activity of the HCSs was investigated for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) by sodium borohydride (NaBH 4 ). The present investigation reveals the outstanding catalytic activity of these particles. The reaction rate followed pseudo-first order kinetics with k value of 4.72 × 10 −3 s −1 and activity parameter of 52.2 s −1 g −1 , which showed superior performance compared to that of metal nanoparticle and metal nanoparticle-carbon hybrid based catalysts.

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 categoriesMeta-epidemiology (narrow)
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 score0.010
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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

Citations11
Published2017
Admission routes2
Has abstractyes

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