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Record W2132701664 · doi:10.1149/1.3089271

Inhibition of Copper Deposition by Polyethylene Glycol and Chloride

2009· article· en· W2132701664 on OpenAlexafffund
Mariano Garrido, Mark Pritzker

Bibliographic record

VenueJournal of The Electrochemical Society · 2009
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of Waterloo
FundersUniversity of WaterlooNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsOverpotentialPolyethylene glycolElectrodePEG ratioDeposition (geology)HysteresisMaterials scienceCathodic protectionCurrent (fluid)ChemistryChemical engineeringAnodeElectrochemistryThermodynamicsOrganic chemistryPhysical chemistryCondensed matter physicsPhysics

Abstract

fetched live from OpenAlex

A comprehensive model for the effect of polyethylene glycol (PEG) and on reduction developed in Part I of this study [ Huerta Garrido and Pritzker , J. Electrochem. Soc. , 156 , D36 (2009) ] is further analyzed in Part II. On the basis of the model, the sharp loss of inhibition at a critical potential during cathodic scans occurs whenever the PEG adsorption density decreases below the minimum amount required to completely cover the electrode. When high additive concentrations are used, the electrode remains completely covered by the inhibiting film throughout the scan and, thus, the current for reduction rises more gradually with overpotential. Excellent agreement between the computed and measured current-potential curves during both forward and reverse directions of cyclic scans is obtained for each solution investigated in this study. Furthermore, analysis of the model reveals that hysteresis in these cyclic scans occurs whenever the electrode goes from a state where it is completely covered by PEG to one where it is only partially covered during the forward scan.

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 score0.011
Threshold uncertainty score0.337

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 head0.002
GPT teacher head0.186
Teacher spread0.184 · 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

Citations29
Published2009
Admission routes2
Has abstractyes

Explore more

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