Investigating adsorption of organic compounds in metal-organic framework MIL-53
Bibliographic record
Abstract
Metal-organic frameworks (MOFs) are versatile materials that incorporate metal centers along with organic linkers in highly ordered, intricate structures. MIL-53 is a MOF that exhibits a “breathing effect,” where the pore size and MOF topology are profoundly influenced by the identity and binding mechanism of guest molecules. This phenomenon renders MIL-53 a promising candidate for sensing applications. In this report, the adsorption of various organic compounds within MIL-53 is investigated using a combination of complementary techniques. Thermal gravimetric analysis experiments confirm loading of the guest molecules and yield insight into adsorption interactions and strengths. Significant guest-induced changes in the crystal structure of MIL-53 are revealed by powder X-ray diffraction experiments; specific unique phases of MIL-53 are related to the identity of the guest molecule and its binding mechanism to the framework. 27Al and 13C solid-state NMR experiments probe the interaction between guest molecules and MIL-53. The relationship between the nature of the guest, the structure of MIL-53, and 27Al NMR parameters is explored. 27Al NMR parameters are sensitive to the host-guest binding mechanism (i.e., hydrogen-bonding or π–π stacking interactions) and yield valuable information regarding the influence of the adsorbates on the local aluminum environment. This combination of physical characterization techniques is a useful probe of guest adsorption and the breathing effect within MIL-53 and should prove useful for investigation of related MOFs.
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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".