Coassembling Mesoporous Zeolitic Imidazolate Frameworks by Directed Reticular Chemistry
Bibliographic record
Abstract
Conventional microporous zeolitic imidazolate frameworks (ZIFs) face limitations in mass transfer and pore accessibility when dealing with large guest molecules. Here, we describe a technique for the synthesis of mesoporous ZIFs (MesoZIFs) using a strategy we term directed reticular chemistry. MesoZIF-8 was prepared through solvent evaporation-induced coassembly of polystyrene- block -poly(ethylene oxide) (PS- b -PEO), ZIF-8 building blocks, and acetic acid (AcOH), followed by amine-facilitated crystallization of ZIF-8 in the interstices of PS- b -PEO micelles. AcOH prevents the fast coordination of ZIF-8 building blocks, avoiding phase separation during coassembly. The employed amine plays a crucial role in neutralizing the crystallization environment and further deprotonating the 2-methlyimizale linker to coordinate with zinc ions. Ink bottle-shaped mesopores with tunable mesopore sizes were created by adjusting the molecular weight of PS- b -PEO. Compared to microporous ZIF-8, MesoZIF-8 exhibited enhanced performance in Knoevenagel condensation reactions involving large reactants and hydrogen storage capacity. With this study, we establish an efficient approach for synthesizing MesoZIFs with highly accessible mesopores to enhance ZIF performance in targeted applications.
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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".