Characterization of oil sands naphthenic acids treated with ultraviolet and microwave radiation by negative ion electrospray Fourier transform ion cyclotron resonance mass spectrometry
Bibliographic record
Abstract
Naphthenic acids (NAs) are concentrated in oil sand process water (OSPW) as a result of caustic oil sands extraction processes. There is considerable interest in methods for treatment of NAs in OSPW. Earlier work has shown that the combination of ultraviolet (UV) and microwave treatments in the laboratory was effective in reducing the concentration of classical NAs. Here we apply Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to further characterize NAs treated with (a) UV (254 nm) in the presence of TiO(2) catalyst; and/or (b) microwave irradiation (2.45 GHz). FT-ICR MS was used to characterize the NA fraction before and after treatment. Acidic oxygen-containing classes were most abundant in all samples whereas other heteroatomic classes were least abundant or not present in some samples. For example, the SO(2)-containing species were absent in UV- or combined UV- and microwave-treated samples. The O(2) class was dominant in all samples, indicative of NAs. However, samples treated with UV and microwave radiation have a lower relative abundance of other heteroatomic classes. We observed O(2), S(1)O(2), O(3), S(1)O(3), O(4), O(5), and O(6) classes, whereas the species with relatively high O(n) content, namely, the O(3), O(5), and O(6) classes, were present only in UV- and microwave-treated samples. The relatively high O(n) content is consistent with oxidation of the parent acids in treated samples. There may thus be potential implications for environmental forensics. For example, the monitoring of the ratio of SO(2):O(2) or tracking the relative abundances of O(2), O(3), O(4), O(5), and O(6) classes may provide insights for distinguishing naturally derived oil sands components from those that are process-related in aquatic environments.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".