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Record W2326642132 · doi:10.1021/jp205052f

High Rate Electrochemical Capacitors from Three-Dimensional Arrays of Vanadium Nitride Functionalized Carbon Nanotubes

2011· article· en· W2326642132 on OpenAlexaff
Li Zhang, Chris Holt, Erik J. Luber, Brian C. Olsen, Huatao Wang, Mohsen Danaie, Xinwei Cui, Xuehai Tan, Vicki W Lui, W. Peter Kalisvaart, David Mitlin

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2011
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceVanadium nitrideCarbon nanotubeNanotechnologyNanocrystalline materialCapacitanceHorizontal scan rateVanadium oxideNitrideElectrolyteElectrodeSupercapacitorCarbon nitrideElectrochemistryChemical engineeringCyclic voltammetryOxideMetallurgy

Abstract

fetched live from OpenAlex

A simple methodology is developed to directly synthesize three-dimensional (3D) electrochemically supercapacitive arrays, consisting of multiwalled carbon nanotubes conformally covered by nanocrystalline vanadium nitride, firmly anchored to glassy carbon or Inconel electrodes. These nanostructures demonstrate a respectable specific capacitance of 289 F g –1, which is achieved in 1 M KOH electrolyte at a scan rate of 20 mV s –1 . The well-connected highly electrically conductive structures exhibit a superb rate capability; at a very high scan rate of 1000 mV s –1 there is less than a 20% drop in the capacitance relative to 20 mV s –1 . Such rate capability has never been reported for VN and is highly unusual for any other oxide or nitride. These 3D arrays also display nearly ideal triangular voltage profiles during constant current charge–discharge cycling. Analysis of the post-electrochemically cycled samples indicates negligible changes occurring in the VN nanocrystallite morphology, but a modification in the structure of the oxidized surface. We envision that the direct synthesis approach employed in this study may serve as a “drop-in” platform for large-scale commercial fabrication of a variety of carbon nanotube-supported functional materials that require excellent electrical conductivity to the underlying support.

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 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 score0.007
Threshold uncertainty score0.867

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)0.0010.000

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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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

Citations160
Published2011
Admission routes1
Has abstractyes

Explore more

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