Impact of Peroxydisulfate in the Presence of Zero Valent Iron on the Oxidation of Cyclohexanoic Acid and Naphthenic Acids from Oil Sands Process-Affected Water
Bibliographic record
Abstract
Large volumes of oil sands process-affected water (OSPW) are produced during the extraction of bitumen from oil sands in Alberta, Canada. The degradation of a model naphthenic acid, cyclohexanoic acid (CHA), and real naphthenic acids (NAs) from OSPW were investigated in the presence of peroxydisulfate (S(2)O(8)(2-)) and zerovalent iron (ZVI). For the model compound CHA (50 mg/L), in the presence of ZVI and 500 mg/L S(2)O(8)(2-), the concentration decreased by 45% after 6 days of treatment at 20 °C, whereas at 40, 60, and 80 °C the concentration decreased by 20, 45 and 90%, respectively, after 2 h of treatment. The formation of chloro-CHA was observed during ZVI/S(2)O(8)(2-) treatment of CHA in the presence of chloride. For OSPW NAs, in the presence of ZVI alone, a 50% removal of NAs was observed after 6 days of exposure at 20 °C. The addition of 100 mg/L S(2)O(8)(2-) to the solution increased the removal of OSPW NAs from 50 to 90%. In absence of ZVI, a complete NAs removal from OSPW was observed in presence of 2000 mg/L S(2)O(8)(2-) at 80 °C. The addition of ZVI increased the efficiency of NAs oxidation by S(2)O(8)(2-) near room temperature. Thus, ZVI/S(2)O(8)(2-) process was found to be a viable option for accelerating the degradation of NAs present in OSPW.
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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 | 0.000 | 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".