Postsynthetic Modification of Zn/Co-ZIF by 3,5-Diamino-1,2,4-triazole for Improved MOF/Polyimide Interface in CO<sub>2</sub>–Selective Mixed Matrix Membranes
Bibliographic record
Abstract
Amine-functionalized zeolite imidazolate frameworks (ZIF) are known to improve the mixed matrix membranes (MMM) separation performances for CO 2 /CH 4 applications. In this study, 3,5-diamino-1,2,4-triazole, a ligand with −NH 2 functionality and uncoordinated −NH group, was used in the postsynthetic modification of dual metal Zn/Co-ZIF for partial substitution of 2-methylimidazole to obtain a biligand Zn/Co-ZIF (Zn/Co-TZ 1h ) with retained crystallinity, tunable pore size and enhanced CO 2 adsorption capacity. A series of mixed matrix membranes were then fabricated at a single concentration (7.5 wt %) of parent Zn/Co-ZIF or Zn/Co-TZ 1h in 6FDA-ODA or Matrimid polyimides to compare the effect of modified ZIF to its unmodified analogue on the MMM properties and CO 2 /CH 4 separation performance. Zn/Co-TZ 1h MMM showed enhanced mechanical properties and better filler integration into the polymer matrix as a result of better interfacial interactions via hydrogen bonding while retaining the same thermal stability as Zn/Co-ZIF MMM. Moreover, the combination of ZIF gate size control, improved size discrimination, and specific chemical interaction gave the NH 2 -functionalized Zn/Co-ZIF MMM the possibility to significantly overcome the CO 2 /CH 4 separation performance of the pure polymer. Postsynthetic modification of ZIF by amine-functionalized ligands can be an effective strategy to improve the filler/polymer interface quality resulting in improved MMM separation properties.
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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".