Surface Properties of Petrologic End-Members from Alberta Oil Sands and Their Relationship with Mineralogical and Chemical Composition
Bibliographic record
Abstract
Clays cause problems in all crucial stages of bitumen extraction, and they affect bitumen recovery and waste management. It is thus of great importance to understand the mineralogy, chemistry, and surface properties of clays to improve both bitumen recovery and tailings treatment. Four petrologically different types of Alberta oil sands ores—called “end-members”—were examined in this study by cation exchange capacity (CEC), specific surface area (SSA), total specific surface area (TSSA), and negative layer charge density (LCD) measurements in order to better understand the effects of clay surface properties on bitumen nonaqueous extraction and solvent recovery from the extraction tailings. The surface properties are primarily controlled by the mineralogy of the petrologic end-members, mainly by the type and quantity of clay minerals. CEC, SSA, TSSA, and LCD increased as the amount of 2:1 clays (illite and illite–smectite), in particular expandable interstratified illite–smectite, increased. CEC values increased with increasing SSA and TSSA. The number of H-aggregates increased and the number of monomers decreased in the second derivative spectra of Rhodamine 6G and Methylene Blue as the 2:1 clays content in the petrologic end-members increased. This indicated a greater negative layer charge density with an increasing amount of 2:1 clays. The molecular aggregation of the organic dyes (Rhodamine 6G and Methylene Blue) was observed in the second derivative spectra for petrologic end-members bearing >25 wt % of 2:1 clays. Overall, the results indicate that interstratified illite–smectite may be largely responsible for high CEC, SSA, TSSA, and LCD in the fine size fractions of petrologic end-members from Alberta oil sands.
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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 | 0.001 | 0.001 |
| 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".