Stability and Disintegration of Ultrathin Heptane Films in Water: Molecular Dynamics Simulations
Bibliographic record
Abstract
Molecular dynamics simulations of ultrathin heptane films (less than 5 nm in thickness) in water were conducted to study their stability and disintegration behavior. The density distributions of heptane and water molecules across the film were determined for different equilibrium film thicknesses ranging from 1.5 to 4 nm. The potential energy of the system was computed as a function of the heptane number fraction, and the results were employed to determine the excess energy of mixing of heptane in water. The diffusion coefficients of heptane and water obtained from the MD simulations were also compared with experimental data. A good agreement was found between the heptane self-diffusivity obtained from the MD simulations and its literature reported value. Following an analysis of the equilibrium properties of the heptane films and associated structures, we performed simulations where the shapes of the heptane films were initially perturbed. Different perturbations of these ultrathin films led to formation of various associated structures, including cylindrical rodlike heptane droplets, films with holes, and intact films. The different shapes are formed in systems with the same heptane/water composition. An analysis of this behavior is presented showing the possibility of multiple associated structures with similar total energy in these highly confined systems.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".