MétaCan
Menu
Back to cohort
Record W2792613531 · doi:10.1002/adfm.201706832

Cavitation Mediated 3D Microstructured Architectures from Nanocarbon

2018· article· en· W2792613531 on OpenAlexafffund
Zishuai Zhang, Siyu Ye, Uwe Gbureck, Jake E. Barralet, Géraldine Merle

Bibliographic record

VenueAdvanced Functional Materials · 2018
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsBallard Power Systems (Canada)McGill University
FundersMinistère du Développement Économique, de l’Innovation et de l’ExportationNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMaterials scienceNanotechnologyMicroscale chemistryOxidizing agentCarbon nanotubeCatalysisChemical engineeringNanoscopic scaleCavitationCathodeConductivityCarbon fibersSpecific surface areaComposite materialComposite numberOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Here, the formation of high surface area microscale assemblies of nanocarbon through phosphate and ultrasound cavitation treatment is reported. Despite high conductivity and large surface area, potential health and safety concerns limit the use of nanocarbon and add challenges to handling. Previously, it is shown that phosphate ultrasonic bonding is ineffective for organic materials but in this study, it is found that by a preliminary oxidizing treatment, several carbons can be readily assembled from xerogels. Assembling nanocarbon into microparticles can usually require a binder or surfactants, which can reduce surface area or conductivity and generate a low microsphere yield. Carbon nanotube microspheres are nitrogen‐doped and flower‐like nanostructured Pt deposited on their surface, and finally showcased as efficient cathode electrocatalysts for the oxygen reduction reaction (half‐wave potential 0.78 V vs reversible hydrogen electrode) and methanol oxidation (417 mA mg −1 ). In particular, no significant degradation of the catalysts is detected after 12 000 cycles (26.6 h). These results indicate the potential of this multimaterial assembly method and open a new way to improve handling of nanoscale materials.

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 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 score0.025
Threshold uncertainty score0.998

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)0.0030.001

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueAdvanced Functional MaterialsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207