Hydrogen storage potential in underground coal gasification cavities: a MD simulation of hydrogen adsorption and desorption behavior in coal nanopores
Bibliographic record
Abstract
Underground hydrogen storage (UHS) in geological formations presents a viable option for long-term, large-scale H2 storage. A physical coal model was constructed based on experimental tests and a MD simulation was used to investigate the potential of UHS in underground coal gasification (UCG) cavities. We investigated H2 behavior under various conditions, including temperatures ranging from 278.15 to 348.15 K, pressures in the range of 5–20 MPa, pore sizes ranging from 1 to 20 nm, and varying water content. We also examined the competitive adsorption dynamics of H2 in the presence of CH4 and CO2. The findings indicate that the optimal UHS conditions for pure H2 involve low temperatures and high pressures. We found that coal nanopores larger than 7.5 nm optimize H2 diffusion. Additionally, higher water content creates barriers to hydrogen diffusion due to water molecule clusters on coal surfaces. The preferential adsorption of CO2 and CH4 over H2 reduces H2-coal interactions. This work provides a significant understanding of the microscopic behaviors of hydrogen in coal nanopores at UCG cavity boundaries under various environmental factors. It also confirms the feasibility of underground hydrogen storage (UHS) in UCG cavities.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".