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Record W2016066458 · doi:10.1149/1.3532311

Voltammetric Modeling of the Kinetics Involved in the Nickel Deposition onto Nickel

2010· article· en· W2016066458 on OpenAlexafffund
Jorge Vázquez-Arenas, Liliana Altamirano-Garcia, Rosa María Luna-Sánchez, R. Cabrera‐Sierra

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsTafel equationNickelChemistryDeposition (geology)DiffusionNickel sulfideKineticsReduction (mathematics)Inorganic chemistryElectrochemistryMass transferSolution of Schrödinger equation for a step potentialElectron transferElectrodeAnalytical Chemistry (journal)Chemical engineeringThermodynamicsPhysical chemistryEnvironmental chemistryChromatographyOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

A comprehensive physicochemical model is used to account for the nickel electrodeposition in sulfate media employing a rotating disk electrode. The model accounts for the nickel deposition, H+ and water reduction. These reactions involve the reduction of Ni(II) by two consecutive 1-electron transfer steps and the H+ and water reduction via the two-step Volmer-Tafel mechanism. Diffusion and convection are considered in the mass-transport balances. Reasonable fits of the model to the experimental data were obtained at different NiSO4 concentrations. Further insights of this system show that the reduction process starting from the open circuit potential to more negative potentials occurs in the following order: H+ reduction, nickel deposition and water reduction. The computation of other variables involved in the model such as the surface pH and concentrations provide additional support to those finds elucidated with the model.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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 designSimulation or modeling
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
Published2010
Admission routes2
Has abstractyes

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Same venueECS TransactionsSame topicElectrodeposition and Electroless CoatingsFrench-language works237,207