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Record W2971679840 · doi:10.1021/acsaem.9b01195

Holey C@ZnFe<sub>2</sub>O<sub>4</sub> Nanoflakes by Carbon Soot Layer Blasting Approach for High Performance Supercapacitors

2019· article· en· W2971679840 on OpenAlexafffund
Madagonda M. Vadiyar, Shubhangi B. Bandgar, Sanjay S. Kolekar, Jia‐Yaw Chang, Yong‐Chien Ling, Zhibin Ye, Anil V. Ghule

Bibliographic record

VenueACS Applied Energy Materials · 2019
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsSupercapacitorMaterials scienceCapacitanceElectrolyteGrapheneElectrodeCarbon fibersNanomaterialsChemical engineeringNanotechnologySootEnergy storageComposite materialComposite numberCombustionChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Holey nanomaterials have been explored as superior electrode materials for energy storage devices. However, the existing methods for synthesis of holey materials are often too complicated and are limited mainly to graphene-derived holey 2D nanosheets. Herein, we report for the first time a versatile, efficient, and low-cost camphor carbon soot layer blasting approach for the generation of nanoholes in C@ZnFe2O4 nanoflakes without damaging the original nanoflake morphology. In the three-electrode system, the holey C@ZnFe2O4 nanoflake based electrode exhibits a high specific capacitance of 1452 F g–1 at 1 A g–1 and excellent cyclic stability with 96% of capacitance retention over 50 000 cycles in 6 M KOH electrolyte. In addition, a symmetric supercapacitor fabricated using two holey C@ZnFe2O4 nanoflake electrodes with [EMIM][BF4] electrolyte exhibits high capacitance (190 F g–1 at 1 A g–1), high energy density (81.4 Wh kg–1 at power density of 0.87 kW kg–1), and superlong cyclic stability (96% retention over 50 000 cycles), which indicates the excellent stability of holey C@ZnFe2O4 nanoflakes in ionic liquid. The carbon soot layer blasting approach developed herein is also extendable for other nanostructures obtained from different metal oxides and sulfides. Thus, the present work provides a significant advancement in synthesis of holey nanomaterials for high-performance energy storage devices.

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 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 score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.010
GPT teacher head0.189
Teacher spread0.178 · 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

Citations22
Published2019
Admission routes2
Has abstractyes

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