Molecular modeling of initiation of interlayer swelling in Na–montmorillonite expansive clay
Bibliographic record
Abstract
Expansive soils are found in many parts of the world. A major constituent of these clays is the mineral montmorillonite. Molecular interactions between clay, cations, and water play an important role in swelling. Molecular models of Na–montmorillonite clay are constructed, and solvation studies are conducted using molecular dynamics. Analysis of molecular trajectories, conformations, and interaction energies reveal key mechanisms that initiate interlayer swelling. In the initially dry interlayer, the interlayer collapses due to strong attractive interactions between Na ions and clay sheets. The van der Waals (vdW) radii of the oxygen atoms further reduce available spacing, thus preventing water molecules from entering the interlayer. Further, it was found that clays, when slightly hydrated, allowed flow of water molecules into the interlayer. The speed of water molecules in the interlayer is found at various time intervals, and the speed decreases with time. The simulations elucidate that Na ions have strong attractive interactions with water molecules and are important initially for attracting water molecules into the interlayer and initiate swelling. Subsequently, after the formation of the hydration shell, flow of water molecules continues, potentially through the hydrogen bond network. These studies provide a clear insight into the molecular mechanisms at the beginning of swelling.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".