Physisorption of molecular hydrogen in curved carbon nanomaterials: a computational study
Bibliographic record
Abstract
Hydrogen physisorption on carbon nanomaterials is a promising method of hydrogen storage because carbon materials are cheap, abundant and light weight.However, storage is difficult because dispersion forces between C and H are weak.Curved carbon substrates are more promising than planar systems because the increased level of sp 3 -hybridization enhances H 2 physisorption.The present study uses density functional theory to model large fullerenes, single-walled carbon nanotubes and graphene to investigate the interaction with H 2 ; decorating platinum is also considered.We conclude that H 2 can be stored in fullerenes without an energy input if the H 2 molecules are more than 3 Å from the carbon surface and more than 2 Å from each other.In addition, confinement effects are observed when hydrogen is stored in fullerenes rather than nanotubes -storage in nanotubes is more favourable for systems with small diameters.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".