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Record W4251475773 · doi:10.1149/ma2020-01211258mtgabs

Lowering the Energy Consumption of Zinc Electrowinning By Electrocatalysis of Oxygen Evolution Reaction Using Manganese Oxides

2020· article· en· W4251475773 on OpenAlexaff
Sheida Arfania, Pei Yu, Pooya Hosseini Benhangi, Edouard Asselin, Előd Gyenge

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicElectrodeposition and Electroless Coatings
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsElectrowinningOverpotentialZincOxygen evolutionMaterials scienceManganeseMetallurgyAnodeInorganic chemistryElectrolyteChemistryElectrodeElectrochemistry

Abstract

fetched live from OpenAlex

Zinc has a wide range of commercial applications including but not limited to galvanizing iron and steel and production of various metal alloys such as brass and bronze. In hydrometallurgical processes, zinc electrowinning from sulfate-based electrolytes is the last step of zinc extraction in which high purity metallic zinc is electrodeposited from a highly acidic solution on an aluminum cathode. The electrowinning stage is very energy-intensive and responsible for approximately 80% of the power requirement of a zinc refinery (1). Thus, improving the energy efficiency and lowering the operating costs of zinc electrowinning are of primary significance. The oxygen evolution reaction (OER) overpotential on conventional lead-silver (Pb-Ag) anodes contributes to nearly 25% of the total electrowinning cell potential (2). Therefore, the high anodic OER overpotential places a heavy financial burden on zinc refining plants. The present study aims to evaluate novel anodic electrocatalysts incorporating MnO x in order to lower the anodic OER overpotential of the zinc electrowinning process. Anodically electrodeposited MnO x catalysts on Pb-Ag electrodes were prepared using galvanostatic and potentiodynamic polarizations. The OER catalytic activity and stability of MnOx electrodeposited Pb-Ag electrodes were evaluated in 160 g/L sulphuric acid solution with 3 g/L of manganese (II) and in the absence and presence of 0.3 g/L of chloride ion at 35°C, using a standard three-electrode setup. The electrolyte composition and operating conditions were selected such that to be directly applicable to the industrial zinc electrowinning process. The OER activity of the MnOx electrodeposited electrodes was investigated through potentiodynamic polarization and 72-hour galvanostatic electrolysis at 50 mA/cm2 superficial current density. Finally, the activity of MnOx electrodeposited Pb-Ag electrodes was explored in a full zinc electrowinning cell through 24-hour galvanostatic electrolysis at 50 mA/cm2 superficial current density. The OER potential variations of the bare Pb-Ag and MnO x electrodeposited Pb-Ag anodes during the 72-hour galvanostatic polarization are shown in Fig. 1. In the absence and presence of chloride ions, the three MnO x electrodeposited Pb-Ag electrodes are observed to reduce the anodic potential by maximum of 150 mV and 90 mV, respectively. Investigation of these novel electrodes in the full-cell zinc electrowinning operation corroborated the half-cell experiments, revealing a maximum of 80 mV reduction in cell potential at 50 mA/cm2 superficial current density and in the presence of 0.3 g/L of chloride ion. Thus, this work demonstrates that MnO x electrodeposited Pb-Ag anodes have great capacity to lower the power consumption of the zinc electrowinning process. Fig. 1. OER activity and stability comparison under galvanostatic polarization for four anodes: bare Pb-Ag (baseline) and three MnOx electrodeposited Pb-Ag anodes prepared via linear scan voltammetry (LSV), constant current density (CCD), and cyclic voltammetry (CV). Superficial current density: 50 mA/cm2. Electrolyte:160 g/L H2SO4 with 3 g/L Mn2+ and 0.3 g/L Cl- at 35°C. References 1. A. C. Scott, R. M. Pitbaldo, G.W. Barton, A. R. Ault, J. Appl Electrochem, 18, 120–127 (1988). 2. S. Schmachtel, M. Toiminen, K. Kontturi, O. Forsen, M. H. Barker, J. Appl Electrochem, 39, 1835–1848 (2009). Figure 1

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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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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