Effect of Voltage on the Treatment of Cyanide Wastewater by Three-dimensional Electrode
Bibliographic record
Abstract
The effects of applied voltage on cyanide wastewater treatment by three-dimensional electrodes were primarily examined. The main electrodes were produced from self-made coal-based electrode materials, and activated carbon was used as a particle electrode to treat cyanide wastewater. Changes in the concentration of ions in wastewater were determined and analyzed through Scanning Electron Microscopy and Energy Dispersive Spectroscopy. Results show that voltage significantly affects wastewater treatment via the three-dimensional electrodes. In particular, the removal rate of the ions in wastewater increases as voltage increases. The reaction mechanism of the three-dimensional electrodes also varies at different voltages. At 1 V, the reaction mechanism of the three-dimensional electrodes involves electro-adsorption. The removal rates of CNT, Cu, Zn, SCN−, and CN− in wastewater are 31.81%, 53.04%, 36.11%, 29.05%, and 29.05%, respectively. The reaction mechanism of the three-dimensional electrodes includes electro-adsorption and enrichment precipitation when voltage is increased to 2 V. The three-dimensional electrode plays a significant role in electrolytic deposition when voltage is further increased to 3 and 4 V. Cu, Zn, and other heavy metal ions are reduced on the cathode and on the particle electrode surface, and the removal rates of CNT, Cu, Zn, SCN−, and CN− in wastewater are 93.94%, 95.22%, 97.23%, 99.38%, and 94.93%, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".