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High performance asymmetric redox capacitor utilizing all oxidation states of vanadium

2025· article· en· W4412429069 on OpenAlexafffund
Mohammad Bandpey, Ej Lung, Dominik P. J. Barz

Bibliographic record

VenueJournal of Power Sources · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVanadiumRedoxCapacitorChemistryMaterials scienceInorganic chemistryChemical engineeringElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

Redox capacitors are promising hybrid energy storage systems able to deliver simultaneously high power and energy densities. Here, we present a novel design of an asymmetric hybrid device utilizing all four oxidation states of vanadium while using a vanadyl sulfate additive electrolyte, and two differently sized high-surface area graphene electrodes. The asymmetric design delivers high gravimetric capacities of 2555 and 1400 mAh g −1 at current densities of 5 and 20 A g −1 , respectively. The performance is significantly higher than that of a similar symmetric hybrid utilizing only three vanadium oxidation states. In terms of cycling stability, the superior performance is maintained for approximately 1100 charge and discharge cycles before capacity decay diminishes the advantages of the asymmetric design. Degradation studies indicate that the cycling performance losses can be attributed to shuttling of V 2+ ions between electrodes, and respective side-reactions which produce inactive vanadium oxides at the electrode. The electrochemistry in our novel asymmetric redox capacitor is similar to an all vanadium-redox flow battery (VRFB). Thus, this study can increase understanding of VRFB degradation mechanisms while proposing an alternative electrolyte with less complexity and maintenance requirements.

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 score0.570
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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

Citations5
Published2025
Admission routes2
Has abstractyes

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