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Record W2042421646 · doi:10.1021/cm010721c

Electrochemical Properties of Ruthenium-Based Nanocrystalline Materials as Electrodes for Supercapacitors

2002· article· en· W2042421646 on OpenAlexaff
Patrick Soudan, Julie Gaudet, Daniel Guay, Daniel Bélanger, Robert Schulz

Bibliographic record

VenueChemistry of Materials · 2002
Typearticle
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsHydro-QuébecInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsNanocrystalline materialMaterials scienceCrystalliteSupercapacitorElectrochemistryChemical engineeringRuthenium oxideOxideBall millSpecific surface areaRutheniumAgglomerateElectrolyteElectrodeMetallurgyNanotechnologyComposite materialChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Nanocrystalline Ti x Fe y Ru z O n materials were prepared by mechanical alloying using high-energy ball milling. The electrochemical properties of the materials were investigated in 1 M NaOH and 1 M H 2 SO 4 aqueous solutions, using a composite electrode technology. The tested materials fall in two categories. On one hand, when the O/Ti ratio is larger than 1, Ru atoms are found in an hexagonal phase. Upon cycling in H 2 SO 4 or NaOH, these materials exhibit a significant increase of their capacitance from ∼5 to ∼50 F/g. This is due to the progressive growth of a ruthenium oxide layer at the surface. On the other hand, when the O/Ti ratio is smaller than 1, Ru atoms are found in a cubic phase (CsCl), along with Ti and Fe atoms. In that case, the growth of a stable oxide phase at the surface of the material occurs only when it is cycled in basic electrolyte. The maximum attainable capacitance is also close to 50−60 F/g. The individual crystallites of as-milled nanocrystalline materials suffer from a strong tendency to agglomerate together. For example, it is shown that the electrochemically active surface area of nanocrystalline RuO 2 is only increased by a factor of 2 when the crystallite size is decreased from 600 to 15 nm, which amounts to a 40-fold increase of the specific surface area. Thus, higher surface area materials were obtained by performing an additional milling step with Al, which is followed by a subsequent leaching of Al with a NaOH solution. With that procedure, the best performances were obtained with leached Ti 2 FeRuO 2, with a maximum capacitance of 110 F/g.

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), Insufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.216
Teacher spread0.195 · 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

Citations147
Published2002
Admission routes1
Has abstractyes

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