Wetting behaviors of water on kerogen surfaces from molecular level: Implication for gas extraction and hydrogen storage in shale
Bibliographic record
Abstract
Shale formations serve as primary reservoirs for natural gas and emerging candidates for hydrogen storage, where the wetting behaviors of organic matter (i.e., kerogen) play a critical role in fluid retention and transport. This study employed molecular dynamics simulations to investigate the pressure-dependent wettability of kerogen surfaces in H2 and CH4 environments under geological conditions (333 K, 10-100 MPa). Results reveal distinct gas-specific mechanisms governing wettability evolution. For CH4-H2O systems, increasing pressure induces a wettability transition from weakly water-wet to gas-wet due to the strong interaction between CH4 and the kerogen surfaces, which results in a smaller gas-solid interfacial tension compared with liquid-solid interfacial tension . Meanwhile, both the reduced gas-liquid and gas-solid interfacial tension contributes to a linear rise in contact angles (88° to 119°). In contrast, H2 exhibits weaker interactions with the kerogen surfaces and experiences a minimal decrease in gas-liquid interfacial tension, thus presenting persistently water-wet characteristics (53° to 69.5°) even at 100 MPa. Crucially, the Young-Laplace equation remains valid at the nanoscale, as evidenced by direct capillary pressure measurements aligning with theoretical predictions, confirming classical interfacial thermodynamics govern nanoconfined fluid behavior. These mechanistic insights elucidate how gas-specific molecular interactions dictate shale wettability, providing a physicochemical basis for optimizing CH4 recovery through pressure-managed wettability alteration and ensuring H2 storage security in hydrophobic kerogen network. Document Type: Original article Cited as: Zhang, M., Huang, J., Wang, H., Niu, W. Wetting behaviors of water on kerogen surfaces from molecular level: Implication for gas extraction and hydrogen storage in shale. Capillarity, 2025, 14(3): 72-81. https://doi.org/10.46690/capi.2025.03.02
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".