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Record W4412509729 · doi:10.1149/ma2025-016707mtgabs

Zinc Anode Self-Corrosion in Aqueous Sulphate Electrolytes: A Respirometric Study

2025· article· en· W4412509729 on OpenAlexaboutno aff
Elnaz Bahmani, Mark Bruns, Michael Strebl, Sannakaisa Virtanen

Bibliographic record

VenueECS Meeting Abstracts · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsnot available
Fundersnot available
KeywordsCorrosionAnodeGalvanic anodeElectrolyteAqueous solutionZincMetallurgyMaterials scienceChemistryInorganic chemistryCathodic protectionElectrode

Abstract

fetched live from OpenAlex

Rechargeable Zn-ion batteries are targeted for non-portable applications, such as grid-scale energy storage, and provide several advantages over the Li-ion batteries currently used for these applications, including safety due to the aqueous electrolytes employed, while relying on Zn that is inexpensive, non-toxic and mined/produced within Canada. Parasitic corrosion reactions (self-corrosion) of the negative Zn electrode (anode during discharge) are problematic since they limit cycle life and produce hydrogen gas (pre-mature pressure-induced failure). The objective of this study was to determine the extent to which parasitic self-corrosion reactions of the negative Zn electrode occur during cycling under both aerated and deaerated conditions This was achieved using a custom-built, in-situ respiratory technique to measure relative changes in hydrogen and oxygen gas composition during corrosion of Zn during bulk immersion in Na 2 SO 4 (aq) and ZnSO 4 (aq) under open-circuit and charge/discharge cycling conditions. X-ray photoelectron spectroscopy (XPS) was used to characterize the structure and composition of the surface films formed. The results are discussed within the context of how cathode reactions are affected by surface film formation.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.077
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.275
Teacher spread0.262 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueECS Meeting AbstractsSame topicCorrosion Behavior and InhibitionFrench-language works237,207