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Cathodic electrosynthesis of VOx ceramics for supercapacitor applications

2025· article· en· W4409912181 on OpenAlexafffund
Dalue Tang, Ri Chen, Chengwei Zhang, Zhenhao Tao, Sofia Czerny-Holownia, Mohamed Nawwar, Hatem S. Zurob, Igor Zhitomirsky

Bibliographic record

VenueCeramics International · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceElectrosynthesisSupercapacitorCathodic protectionCeramicMetallurgyElectrochemistryElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

The feasibility of electrosynthesis of VO x by the cathodic electrogenerated base method is demonstrated and advantages of this technique are discussed. The electrogenerated base method results in the fabrication of VO x material, containing V 3+ , V 4+ and V 5+ species from VOSO 4 solutions. The deposition yield is studied in-situ at a constant voltage or constant current conditions using a quartz crystal microbalance. The method allows rigid control of the deposition yield. The results of X-ray photoelectron spectroscopy, thermogravimetic and differential thermal analyses allow the development of the new electrosynthesis mechanism. For the first time electric discharge machining (EDM) is used for the fabrication of patterned Ni current collectors for VO x supercapacitors. VO x material shows capacitive behavior in the positive potential range with a capacitance of 278.6 mF cm −2 . Asymmetric device containing VO x cathodes and γ-Fe 2 O 3 anodes shows a capacitance of 27.1 mF cm −2 in a voltage window of 1.5 V in Na 2 SO 4 electrolyte. The approach developed in this investigation opens an avenue for the fabrication of advanced patterned ceramic asymmetric supercapacitors with enlarged voltage windows.

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 score0.200
Threshold uncertainty score0.528

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)0.0000.000

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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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