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Record W4412511746 · doi:10.1149/ma2025-01201363mtgabs

The Diffusion Potential and Impedance Behaviour Associated with an Anodic Metal Dissolution Reaction

2025· article· en· W4412511746 on OpenAlexaff
Roger Newman, Anatolie G. Carcea

Bibliographic record

VenueECS Meeting Abstracts · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDissolutionDiffusionElectrical impedanceAnodeMetalMaterials scienceChemistryThermodynamicsMetallurgyElectrodePhysical chemistryElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

The authors have read many textbook formulations of the DC and AC response of an anodically dissolving metal electrode (with no extraneous cathodic reactions such as water reduction), and we believe - rightly or wrongly - that most of these miss one or more important points. Under steady state DC anodic dissolution conditions, we can assume that the net anodic current density is affected by the basic kinetic parameters of the partial reactions, and by the concentration of the product cations at the electrode. One outcome of such an assumption is that the reaction may appear to obey Tafel's law, but with a different (apparent) b value from that of either the dissolution or deposition reaction taken individually. This is a very easy derivation, but does not appear in most sources. For example, dissolution of Ag in aqueous perchloric acid at room temperature shows an apparent b value of about 60 mV, yet it is well known that a rate-determining single electron transfer should give a b value of about 120 mV, for either direction of the reaction. For AC measurements, one should beware of using the wrong formulation of the "Warburg" impedance. Most textbook derivations are for dissolved species only (such as ferricyanide and ferrocyanide mixtures), not for a process involving a solid metal electrode. A very simple model can be derived using similar assumptions to the DC case, and can be tested experimentally with good results.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.232
Teacher spread0.226 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueECS Meeting AbstractsSame topicAnodic Oxide Films and NanostructuresFrench-language works237,207