Corrosion Assessment of Lead Anodes in Nickel Electrowinning
Bibliographic record
Abstract
Due to their insolubility, lead and its alloys have always been candidates for anodes in electrowinning plants. However, corrosion problems associated with lead anodes cost millions of dollars for industries annually. Cast and rolled lead-silver and lead-calcium anodes were tested under typical nickel electrowinning conditions. Effects of sulfuric acid and chloride concentrations on overall corrosion performance of the anode materials were investigated. Moreover, oxygen evolution reaction rate and overpotential were determined for specific electrode material/solution conditions. Galvanostatic experiments were performed so the actual conditions that the electrodes are exposed to were simulated. Corrosion rates of the electrodes were calculated using the discharge plateau recorded during OCP measurements following the galvanostatic experiments. SEM and XRD were used to study the correlation between the surface morphology of the electrodes, their phase composition and their corrosion rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".