Effective Interactions and Adsorption of Heterocyclic Aromatic Hydrocarbons in Kaolinite Organic Solutions Studied by 3D-RISM-KH Molecular Theory of Solvation
Bibliographic record
Abstract
We employ the molecular theory of solvation also known as the three-dimensional reference interaction site model with the Kovalenko–Hirata closure relation (3D-RISM-KH) to study adsorption of several heterocyclic aromatic hydrocarbons (acridine, benzothiophene, carbazole, dibenzothiophene, indole, and phenanthridine), which are intended to represent bitumen fragments on the surfaces of a single-sheet kaolinite nanoparticle in cyclohexane and toluene solvents. In addition to adsorption, we also examine solvent-mediated effective interactions between two kaolinite nanoparticles in organic and aqueous solutions. The proposed adsorption model serves as a simple prototype of suspensions formed during nonaqueous extraction of bitumen from oil sands of the Athabasca Basin. Using the proposed computational approach, excess adsorption isotherms of bitumen fragments on two different faces of kaolinite were calculated and compared in cyclohexane and toluene solvents at several temperatures. Almost all the studied molecules show strong preference for adsorption on the octahedral aluminum hydroxide surface of kaolinite. While adsorption of the molecules on the tetrahedral silicon oxide surface is weaker, it is still significant compared to the octahedral surface and for some of the studied molecules adsorption appears to be stronger than for the octahedral surface. Due to the better surface and bulk solvation properties of toluene, the adsorption of the bitumen fragments in toluene is weaker than in cyclohexane. Potentials of mean force between kaolinite nanoplatelets in cyclohexane at several temperatures were calculated using the 3D-RISM-KH molecular theory of solvation. Evaluation of effective interactions by conventional molecular simulation techniques generally requires costly free energy integration and therefore is usually avoided by adopting simple and often unrealistic semiempirical effective potentials. On the other hand, the 3D-RISM-KH molecular theory of solvation offers a fully atomistic description with all-atom force fields and notable performance advantages over molecular simulations. Obtained in this way potentials of mean force in organic solvents exhibit complex oscillating behavior and generally possess deeper main minima and smaller aggregation barriers than the corresponding potentials in aqueous solution.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".