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Record W1991612755 · doi:10.1039/c3ta15255c

Mesoporous nitrogen-doped carbon from nanocrystalline chitin assemblies

2014· article· en· W1991612755 on OpenAlexafffund
Thanh‐Dinh Nguyen, Kevin E. Shopsowitz, Mark J. MacLachlan

Bibliographic record

VenueJournal of Materials Chemistry A · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceChemical engineeringNanocrystalline materialChitinMesoporous materialSupercapacitorCarbon fibersNanorodCarbonizationNanotechnologyComposite materialOrganic chemistryChitosanElectrodeComposite numberChemistryElectrochemistryCatalysisScanning electron microscope

Abstract

fetched live from OpenAlex

Nanocrystalline chitin has been used both as a soft template and as the carbon and nitrogen sources for preparing mesoporous nitrogen-doped carbon materials with a layered structure. The chitin nanorods prepared by sequential deacetylation and hydrolysis of fibrils isolated from king crab shells organized into a nematic liquid-crystalline phase. Silica/chitin composites obtained by sol–gel condensation of silica in the presence of liquid-crystalline chitin were carbonized and etched to yield mesoporous nitrogen-doped carbon films that replicate the layered nematic organization of the nanocrystalline chitin films. The high degree of mesoporosity and nitrogen doping in the liquid-crystalline biopolymer-derived carbon replicas allows them to function as efficient supercapacitor electrode materials. Films embedded with tin oxide nanoparticles displayed superior performance for supercapacitor electrodes.

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 categoriesInsufficient 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 score0.004
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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

Citations90
Published2014
Admission routes2
Has abstractyes

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