Exploring Host–Guest Interactions in the α-Zn<sub>3</sub>(HCOO)<sub>6</sub> Metal-Organic Framework
Bibliographic record
Abstract
Abstract Metal-organic frameworks (MOFs) are promising gas adsorbents. Knowledge of the behavior of gas molecules adsorbed inside MOFs is crucial for advancing MOFs as gas capture materials. However, their behavior is not always well understood. In this work, carbon dioxide (CO2) adsorption in the microporous α-Zn3(HCOO)6 MOF was investigated. The behavior of the CO2 molecules inside the MOF was comprehensively studied by a combination of single-crystal X-ray diffraction (SCXRD) and multinuclear solid-state magnetic resonance spectroscopy. The locations of CO2 molecules adsorbed inside the channels of the framework were accurately determined using SCXRD, and the framework hydrogens from the formate linkers were found to act as adsorption sites. 67Zn solid-state NMR (SSNMR) results suggest that CO2 adsorption does not significantly affect the metal center environment. Variable-temperature 13C SSNMR experiments were performed to quantitatively examine guest dynamics. The results indicate that CO2 molecules adsorbed inside the MOF channel undergo two types of anisotropic motions: a localized rotation (or wobbling) upon the adsorption site and a twofold hopping between adjacent sites located along the MOF channel. Interestingly, 13C SSNMR spectroscopy targeting adsorbed CO2 reveals negative thermal expansion (NTE) of the framework as the temperature rose past ca. 293 K. A comparative study shows that carbon monoxide (CO) adsorption does not induce framework shrinkage at high temperatures, suggesting that the NTE effect is guest-specific.
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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 | 0.000 |
| 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".