A Comprehensive Analysis of Organic Matter Removal from Clay-Sized Minerals Extracted from Oil Sands Using Low Temperature Ashing and Hydrogen Peroxide
Bibliographic record
Abstract
Understanding mineralogy and surface properties of clays is very vital in oil sands processing and tailings management. Clay-sized minerals (CSM) in oil sands are often contaminated by tightly adsorbed organics during hydrocarbon removal, thereby increasing surface hydrophobicity and making characterization of CSM problematic. This study evaluates the use of low temperature ashing (LTA) and hydrogen peroxide (H 2 O 2 ) for the removal of adsorbed organic matter (OM) from CSM without changing its mineralogy. CSM isolated from tailings and bitumen froth of a Denver flotation cell after oil sands extraction was treated by H 2 O 2 and LTA. Both techniques were found to be effective in removing OM from the CSM as shown by the infrared spectra of the samples. The wettability of the CSM increased with treatment. Elemental analysis showed a reduction in carbon, hydrogen, and nitrogen. Infrared band for siderite at 864 cm −1 was observed for the isolated and LTA-treated CSM but was absent for those treated by H 2 O 2 . The absence of siderite in the X-ray diffraction patterns of the H 2 O 2 -treated CSM further substantiates its oxidation by H 2 O 2 . Cation exchange capacity of model clays and samples was found to be unaffected by LTA treatment, unlike those treated with H 2 O 2 . Overall, LTA appears to be a more suitable method than H 2 O 2 for organic matter removal from the isolated CSM because of its selectivity for decomposing only organics.
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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".