Electrometallurgical recovery of nickel and vanadium from spent desulphurization catalysts using an acidic leaching–electrolysis technique
Bibliographic record
Abstract
Abstract Spent desulphurization catalysts are considered a major secondary source of valuable metals. The contents of nickel and vanadium present in these catalysts, accompanied by environmental rules, have attracted scientists to explore diverse options for their effective processing. The electrometallurgy recovery of Ni and V from the spent desulphurization Ni‐Mo‐V/Al 2 O 3 catalyst is described in this study. Using flat plate graphite electrodes, the electrochemical deposition of Ni and V from spent catalyst in an acid solution (HNO 3 /H 2 SO 4 ) was investigated. By the central composite design of the response surface methodology, the effect of the operating factors was examined and optimized. At the ideal conditions of reaction temperatures of 84.0 and 42.0°C, electrolysis times of 5.6 and 4.4 h, liquid/solid ratios of 22.7 and 15.4 ml/g, and current densities of 229.0 and 255.6 A/m 2 , respectively, the recovery efficiencies of Ni and V were 81.96% and 93.07%. The statistical analysis revealed that the expected data ( R 2 = 0.9984 and R 2 = 0.9883) were in good agreement with the observed data ( R 2 = 0.9984), with an average variation from experimental data of 0.78% and 0.65% for the optimum conditions of Ni and V recovery, respectively. It shows that the Ni and V nanoparticles deposited have a spherical form with purities of 84.39% and 90.76%, respectively. Because of its great efficiency and purity, the current study can provide a dependable procedure for extracting Ni and V from solid waste.
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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".