UV Photocatalytic Degradation of Commercial Naphthenic Acid Using TiO<sub>2</sub>-Zeolite Composites
Bibliographic record
Abstract
The presence of naphthenic acids in oil sand products and process streams is the cause of toxicity to aquatic life and corrosion. The removal of organic acids from tailings pond water reduces the negative impact on marine life. The ultra-violet (UV) photocatalytic reduction of commercial naphthenic acid in water using TiO2-zeolitecomposites showed a significant decrease in the concentration of naphthenic acid, accompanied by an increase in carbon dioxide formation; the presence of carbon dioxide signifies degradation of the naphthenic acids. Mixtures of the acid and photocatalyst kept in the dark did not show any concentration changes. The extent of naphthenic acid reduction by UV light was verified by the reduction in total acidity. The total acidity values of mixtures of the acid and TiO2-zeoliteexposed to UV decreased by 31% compared to mixtures kept in the dark. A reduction in total acidity may lead to a decrease in the toxicity of naphthenic acid contaminated water.
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.
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 | 0.000 | 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 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".