Removal of COD and colour in real pharmaceutical wastewater by photoelectrocatalytic oxidation method
Bibliographic record
Abstract
In this study, TiO2/Ni photo-anode and multi-walled carbon nano-tubes (MWCNTs) air cathode were prepared by the dip-coating method, and the photoelectrocatalytic degradation of real pharmaceutical wastewater was investigated in the self-made reactor. The combination of the TiO2/Ni electrode and MWCNTs air cathode was adopted to treat the pharmaceutical wastewater by the process of photoelectrocatalysis. Various operational parameters to achieve optimum efficiency of this photoelectrocatalytic degradation system are presented, such as applied bias voltage, NaCl concentration, pH and different degradation methods. Under the optimal conditions, the removal of chemical oxygen demand (COD) and colour are 93.5% and 78.5% respectively. The possible roles of the anode-cathode on the reactions and the probable mechanisms of effect were also discussed. The photoelectrocatalytic technology can be used for the long-term treatment of real pharmaceutical wastewater.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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 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".