Metal–Inorganic–Organic Matrices as Efficient Sorbents for Hydrogen Storage
Bibliographic record
Abstract
Stabilization of metal nanoparticles (MNPs) without re-aggregation is a major challenge. An unprecedented strategy is developed for achieving high dispersion of copper(0) or palladium(0) on montmorillonite-supported diethanolamine or thioglycerol. This results in novel metal-inorganic-organic matrices (MIOM) that readily capture hydrogen at ambient conditions, with easy release under air stream. Hydrogen retention appears to involve mainly physical interactions, slightly stronger on thioglycerol-based MIOM (S-MIOM). Thermal enhancement of desorption suggests also a contribution of chemical interactions. The increase of hydrogen uptake with prolonged contact times arises from diffusion hindrance, which appears to be beneficial by favoring hydrogen entrapment. Even with compact structures, MIOMs act as efficient sorbents with much higher efficiency factor (1.14-1.17 mmol H 2 m(-2)) than many other sophisticated adsorbents reported in the literature. This opens new prospects for hydrogen storage and potential applications in microfluidic hydrogenation reactions.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".