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Record W2521332230 · doi:10.1149/ma2016-02/7/932

Vanadium Nitride Electrodes: Limitations and Practical Use in Electrochemical Capacitors

2016· article· en· W2521332230 on OpenAlexaff
Thierry Brousse, Alban Morel, Daniel Bélanger, Yann Borjon-Piron

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsVanadium nitrideMaterials scienceElectrolyteElectrodeCapacitanceThin filmElectrochemistryNitrideCapacitorSupercapacitorChemical engineeringFaraday efficiencyAnalytical Chemistry (journal)NanotechnologyChemistryElectrical engineeringLayer (electronics)VoltageChromatography

Abstract

fetched live from OpenAlex

Vanadium nitride has displayed many interesting characteristics for its use as a pseudocapacitive [1] electrode in an electrochemical capacitor, such as good electronic conductivity, good thermal stability, high density and high specific capacitance. Thin films of VN were prepared by D.C. reactive magnetron sputtering. The electrochemical stability of the films as well as the influence of dissolved oxygen in 1 M KOH electrolyte were investigated. In order to avoid material as well as electrolyte degradation, it was concluded that vanadium nitride should only be cycled between -0.4 and -1.0 V vs. Hg/HgO. After a 24 hours stabilization period, the prepared VN thin film showed an initial capacitance of 19 mF.cm-2 and a capacity retention of 96% after 10000 cycles. Furthermore, dissolved oxygen in the electrolyte was demonstrated to cause self-discharge up to a potential above -0.4 V vs. Hg/HgO, where VN was shown to be unstable. Additionally, the presence of oxygen was shown to shift the open circuit potential of a VN electrode to about 0 V through self-discharge processes [2]. Since the performances reached on thin film electrodes are difficult to translate to VN powder, the use of VN thin films in hybrid microdevices has been investigated [3]. Microdevices were designed using VN thin films as negative electrode and electrodeposited Co3O4 as positive electrode in order to combine the high capacity of the Faradaic type cobalt based electrode and the high capacitance and good cycling ability of VN electrode when used in an optimized electrochemical window. The performance of such devices will be reported and discussed with regards to existing literature on the field. References [1] Brousse, T.; Belanger, D.; Long, J. W. J. Electrochem. Soc. 2015, 162, A5185–A5189. [2] Morel, A.; Borjon-Piron, Y.; Lucio Porto, R.; Brousse, T.; Bélanger, D.; J. Electrochem. Soc. 2016, 163, A1077-A1082. [3] Eustache, E.; Frappier, R.; Porto, R. L.; Bouhtiyya, S.; Pierson, J.-F.; Brousse, T. Electrochem. Commun. 2013, 28, 104–106.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.258
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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
Published2016
Admission routes1
Has abstractyes

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