Molecular Dynamics Simulations of Mineral Surface Wettability by Water Versus CO<sub>2</sub>: Thin Films, Contact Angles, and Capillary Pressure in a Silica Nanopore
Bibliographic record
Abstract
Abstract The wettability of mineral surfaces is an important property influencing multiphase flow in soils and sedimentary rocks. In particular, for CO2 abatement technologies that rely on trapping supercritical CO2 in sedimentary formations, the wettability of relevant mineral surfaces by water is a poorly constrained fundamental property influencing stratigraphic and residual trapping. Theoretical studies have noted that adsorbed water films may hold a key to resolving many of the discrepancies in reported wettability data, but the transition from the droplet to the film is difficult to observe experimentally. The link between continuum and nanoscale observations can be elucidated using molecular dynamics (MD) and thermodynamic equations. We simulate water and CO2 at various pressures between quartz surfaces to probe the thickness of the adsorbed water film observed between the CO2 and quartz, and the radius of curvature of the fluid–fluid interface as a function of CO2 pressure. These results are discussed in the context of the relevant interfacial energies and Young’s equation and the Gibbs CO2 surface excesses at various interfaces. We show that the augmented Young–Laplace equation accurately captures the relationship between the observed radius of curvature, the capillary pressure between the bulk fluid phases, and the disjoining pressure in the adsorbed water film. We examine the thermodynamics of thin water films in novel depth and present a new methodology for characterizing circularity approaching a mineral interface and for comparing continuum and nanoscale manifestations of wettability. We find that discrepancies in both the experimental and MD database may be influenced by proximity to solid surfaces and adsorbed wetting films.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".