Enhanced Room-Temperature Hydrogen Physisorption in Zeolitic Imidazolate Frameworks and Carbon Nanotube Hybrids
Bibliographic record
Abstract
In this work, zeolitic imidazolate frameworks (ZIF-8, ZIF-67, and ZC-ZIF) and their hybrid composites with carboxylate-functionalized carbon nanotubes (fCNTs) are synthesized through low-cost synthesis methods for enhanced physisorption-based hydrogen storage at room temperature. While both base and hybrid structures are designed to improve hydrogen uptake, the base materials exhibit the most notable performance compared to their carbon hybrid counterparts. The structural analysis confirms that all samples maintain high crystallinity and exhibit well-defined rhombic dodecahedral morphologies. The hybrid composites, due to the intercalation of fCNTs, show slightly larger particle sizes than their base materials. X-ray photoelectron spectroscopy reveals strong nitrogen–metal coordination in the ZIF structures, contributing to a larger specific surface area (SSA) and optimal microporous properties. A linear fit of SSA and hydrogen uptake indicates improved hydrogen transport at low pressures due to fCNT addition. ZIF-8 achieves the highest SSA of 2023.6 m2/g and hydrogen uptake of 1.01 wt. % at 298 K and 100 bar, with 100% reversible adsorption. Additionally, ZIF-8 exhibits excellent cyclic repeatability, with only 10% capacity reduction after five adsorption/desorption cycles. Kinetic analysis reveals that hydrogen adsorption in the ZIF materials is governed by a combination of surface adsorption, intraparticle diffusion, and complex pore filling. These findings underscore the potential of ZIFs as superior materials for room-temperature hydrogen storage.
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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 | 0.001 |
| 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".