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Record W4411856444 · doi:10.1002/maco.70003

Study of Manganese and Phosphoric Acid on Dimensionally Stable Anodes During Zinc Electrowinning

2025· article· en· W4411856444 on OpenAlex
Fu-Sheng Liu, Georges Houlachi, Sanae Haskouri, Edward Ghali

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials and Corrosion · 2025
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsHydro-QuébecUniversité Laval
Fundersnot available
KeywordsManganeseElectrowinningPhosphoric acidZincAnodeMetallurgyMaterials scienceChemistryElectrode

Abstract

fetched live from OpenAlex

ABSTRACT During zinc electrowinning, the manganese oxide covers the surfaces of the dimensionally stable anodes (DSA) and decreases their electrocatalytic performance. Phosphoric acid is added into the zinc electrolyte to complex the manganic ion and hence reduce its disproportionation to MnO 2 . In the investigation, electrochemical measurements were carried out to examine electrochemical behavior of DSA (Ti/IrO 2 –Ta 2 O 5 ) anode during zinc electrolysis at 48 mA.cm −2 and 39°C. It is observed that the anodic potentials of DSA anodes are much lower after 5 h polarization in the zinc electrolyte containing 35 mL.L −1 phosphoric acid at 39°C than that without phosphoric acid. Also, the current efficiencies increase after addition of phosphoric acid to the zinc electrolyte containing 9 g.L −1 Mn 2+ . Electrochemical noise and impedance measurements show that addition of 35 mL.L −1 H 3 PO 4 to the zinc electrolyte increases the corrosion resistances during polarization. Addition of phosphoric acid to the zinc electrolytic can increase the oxidation peak by cyclic voltammetry study and improve the electrocatalytic behavior of DSA anodes.

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.

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 score0.016
Threshold uncertainty score0.285

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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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