Hydrogen in the Metal−Organic Framework Cr MIL-53
Bibliographic record
Abstract
Practical methods for hydrogen storage are still a major bottleneck in the realization of an energy economy based on hydrogen as an energy carrier. (1) Surface adsorption within crystalline, nanoporous, metal−organic frameworks (MOFs) provides a promising storage method that relies on sufficiently strong adsorption interactions for a large fraction of the storage capacity. Only few MOF structures were studied up to date using neutron diffraction to resolve the adsorption sites. (2-5) Here we use in situ neutron diffraction to characterize hydrogen (deuterium) adsorption sites in the MOF Cr MIL-53. The strongest adsorption interactions are present at three different sites where the hydrogen touches nearby organic linkers from two directions. Perhaps surprisingly, there is no strong direct interaction with the Cr−O cluster. Large breathing modes of the crystalline lattice are observed upon loading hydrogen reversibly to an equivalent of 5.5 wt %. Such breathing modes are known to occur for polar solvents like H 2 O, alkanes, and also for the gas CO 2; however, as shown here it also occurs for weakly van der Waals adsorbed hydrogen molecules.
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 | 0.000 |
| 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) | 0.001 | 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".