Photocatalytic Oxidation of Ni−EDTA in a Well-Mixed Reactor
Bibliographic record
Abstract
EDTA forms a strong complex with a variety of metals. These metal−EDTA complexes are very stable and often inert to conventional biological or chemical treatment methods. Photocatalytic oxidation has shown promising results in oxidizing metal−EDTA complexes. Thus, the objective of this research was to investigate the photocatalytic oxidation of the Ni−EDTA complex. For this investigation, experiments were carried out in a semi-batch reactor equipped with up to four UV lamps (with light intensities varying from 1.6 × 10 -6 to 6.4 × 10 -6 einstein/min). Preliminary studies demonstrated that the photocatalytic degradation of Ni−EDTA could not take place in the absence of a source of light energy, TiO 2, and oxygen. From degradation experiments, it was found that the light energy and catalyst concentration limit the production of the electron/hole pair and thus the degradation of Ni−EDTA. The effect of the initial Ni−EDTA concentration was also investigated. The results display Langmuir−Hinshelwood type kinetic behavior. A similar trend was observed when the dissolved oxygen concentration was varied. The oxygen and Ni−EDTA concentrations were also found to limit the degradation of Ni−EDTA. In all experiments, the total organic carbon (TOC) measurements showed that minimal mineralization of the starting Ni−EDTA took place.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".