Nickel, cyanide, zinc, and copper removal from the effluent using photo-electrocoagulation-oxidation
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.
Bibliographic record
Abstract
• The in-situ generation of ozone significantly improved the pollutants removal rate. • The simultaneous production of oxidizing agents caused the high removal efficiency. • The photoelectrocoagulation method increases ozone production. • The complete removal of copper and cyanide were achieved. • The stainless steel electrode had a significant role on the ozone agent generation. One emerging approach for eliminating organic and inorganic pollutants from wastewater is electrocoagulation, often coupled with traditional methods to enhance efficacy. This study investigates the simultaneous elimination of nickel (Ni), cyanide (CN), zinc (Zn), and copper (Cu) from the natural wastewater of a gold processing plant using the photo-electrocoagulation method with ozone as an oxidizing agent (ECOUV), both in continuous and batch modes, produced in situ. When performing the test in batch mode, CN, Ni, Cu, and Zn were removed at their peak of 100, 79.1, 100, and 89 %, respectively, at pH=10 and at i = 15 mA/cm 2 using graphite-aluminum cathodes and stainless-steel anodes for 60 min without injecting oxidizing agent and solely based on in-situ ozone production. During the continuous mode test, the highest removal efficiencies achieved were 100 % for CN, 73 % for Ni, 100 % for Cu, and 78.8 % for Zn, all under identical operational parameters. These results confirm that ECOUV holds promise as a feasible approach for removing pollutants from the wastewater discharged by mineral processing facilities.
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 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it