Effect of Preheating Treatment on the Measured Heats of Adsorption of Organic Probes on Clays with Different Surface Compositions
Bibliographic record
Abstract
The effect of column preconditioning temperature ( T cp ) on the measured heats of adsorption of selected aliphatic and aromatic compounds for kaolinite and illite, two clay minerals commonly encountered in the oil sands industry, was studied using the technique of inverse gas chromatography (IGC). T cp was varied from 100 to 340 °C. Our results showed that, as T cp was increased from 100 to 170 °C, the heats of adsorption (affinities) of the selected aliphatic solutes for kaolinite increased slightly, but those for illite stayed nearly the same. At higher T cp values (170–230 °C), solute adsorption exhibited essentially no dependence on T cp for both kaolinite and illite. This observation is attributed to the decreasing hydrophilicity for kaolinite from 100 to 170 °C, but not for kaolinite from 170 to 230 °C or for illite from 100 to 230 °C. Higher T cp values (230–340 °C) were used for the two aromatic solutes (benzene and toluene), and it was found that their heats of adsorption for illite were significantly reduced (50%) whereas those for kaolinite were insensitive to T cp . It is believed that this observation can be attributed to the loss of surface water as a result of increasing temperature. Here, departure of surface water would decrease the number of Lewis acid sites on the tetrahedral surfaces, thereby reducing the attractive interaction between the surfaces and the π bonds of the aromatic solutes at elevated T cp . Because illite contains only tetrahedral surfaces, the measured heats of adsorption of benzene and toluene decreased with increasing temperature. However, in the case of kaolinite, which contains 1:1 tetrahedral and octahedral surfaces, this effect was offset by the increasing attractive interaction between the exposed hydroxyl moieties on the octahedral surfaces and the π bonds of the aromatic probes. As demonstrated in this work, the measured heat of adsorption depends on T cp . Therefore, care must be taken when comparing solute affinity for various types of minerals based on IGC measurements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".