A 3D-RISM-KH Molecular Theory of Solvation Study of the Effective Stacking Interactions of Kaolinite Nanoparticles in Aqueous Electrolyte Solution Containing Additives
Bibliographic record
Abstract
We develop a predictive model to study how flocculant additives alter the interactions among clay particles in colloidal suspensions, such as industrial mining tailings. Fully atomistic models of kaolinite nanoplatelets constructed from X-ray crystal structure data feature a highly polarized charge distribution, which defines their solvation, adsorption, and association properties. Effective interactions, in the form of potential of mean force (PMF), between kaolinite platelets in aqueous electrolyte solution are calculated using the three-dimensional reference interaction site model with the Kovalenko–Hirata closure relation (3D-RISM-KH) molecular theory of solvation based on the first-principles of statistical mechanics. This theory is also employed to study the adsorption of ions and flocculant additive building blocks onto kaolinite surfaces. Three main mutual orientations of platelets are studied in aqueous electrolyte solutions of several polymer building blocks represented by acrylamide, acrylic acid, acrylate, and styrene. The results indicate that Na + are predominantly adsorbed onto the siloxane surface of kaolinite while the chloride and acrylate anions prefer the aluminum hydroxide surface of kaolinite. Weaker adsorption preference is observed for the neutral monomers. The PMF between platelets depends nontrivially on the concentration of solvent components and exhibits a complex oscillating behavior with several minima and maxima that correspond to important solvation and aggregation energy barriers. Among the three studied mutual orientations of the nanoplatelets, the most stable one corresponds to the direct contact of the aluminum hydroxide with siloxane surfaces. Other highly probable arrangements correspond to nanoplatelets separated by a single layer of solvent. The effect of additives on interparticle interactions is correlated with the strength of adsorption on kaolinite relative to water, as strongly and weakly adsorbing species cause increase and decrease, respectively, of the PMF at short distances. Moreover, hydrophobic additives cause a decrease in the local solvent density between nanoparticles and consequently a decrease in the PMF. These results provide valuable insights into the mechanism of interactions of kaolinite nanoplatelets in thermodynamic conditions relevant to clay dispersions, as occurring in tailings produced by the process of hot water extraction of bitumen from oil sands and other mining tailings.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".