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Record W2988868515 · doi:10.1149/2.0611915jes

The Susceptibility of Copper to Pitting Corrosion in Borate-Buffered Aqueous Solutions Containing Chloride and Sulfide

2019· article· en· W2988868515 on OpenAlexafffund
Mengnan Guo, Jian Chen, Taylor Martino, Mark C. Biesinger, James J. Noël, David W. Shoesmith

Bibliographic record

VenueJournal of The Electrochemical Society · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsWestern University
FundersNuclear Waste Management Organization
KeywordsSulfideInorganic chemistryChlorideOxideDissolutionChemistryAqueous solutionX-ray photoelectron spectroscopyCopperRaman spectroscopyPitting corrosionElectrochemistryCopper sulfideCorrosionChemical engineeringElectrode

Abstract

fetched live from OpenAlex

The formation of sulfide and oxide films on copper (Cu) was studied in chloride solutions with and without added borate and sulfide. Electrochemical experiments demonstrated that Cu sulfide (Cu2S) films formed at considerably lower potentials than oxides (Cu2O/CuO) films. The growth of Cu2S was controlled by a combination of sulfide transport to the reacting Cu surface and the competition between SH− and Cl− ions for adsorption sites on the Cu surface. Scanning electron microscopy on focused ion-beam cut cross sections demonstrated that the films were porous and not passive. At more positive potentials, Raman spectroscopy and X-ray photoelectron spectroscopy demonstrated that the formation of oxide films, likely with the formation of a passive oxide film, dominated over anodic dissolution of Cu as CuI chloride complexes when the borate to chloride concentration ratio was sufficiently high. If pitting is to occur on Cu, it will require oxide not sulfide film growth.

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 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 score0.006
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.246
Teacher spread0.234 · 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

Citations23
Published2019
Admission routes2
Has abstractyes

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