A 3D Microporous MOF with <i>mab</i> Topology for Selective CO <sub>2</sub> Adsorption and Separation
Bibliographic record
Abstract
Abstract A three dimensional MOF, {[Zn(OBA)(L) 0.5 ].DMA} n ( IITKGP‐7 , IITKGP stands for Indian Institute of Technology Kharagpur), has been synthesized by the combination of a V‐shaped organic acid linker (H 2 OBA=4, 4′‐oxybisbenzoic acid) with flexible N,N‐donor spacer ( L =2,5‐bis(3‐pyridyl)‐3,4 – diaza‐2,4‐hexadiene), forming a network with mab topology (DMA=N, N‐dimethylacetamide). This MOF is characterized by Fourier‐transform infrared spectroscopy (FTIR), elemental analysis (EA), powder X‐ray diffraction (PXRD), thermo gravimetric analysis (TGA) and single crystal X‐ray diffraction. The framework exhibits rhombus‐shaped channels of approximate size of 5.3 Å x 6.4 Å along crystallographic b axis with a potential solvent accessible volume of 31.8%. Gas sorption measurements of the evacuated framework shows preferential uptake of CO 2 at 273 and 295 K under 1 bar over N 2 and CH 4 . Calculations based on ideal adsorbed solution theory (IAST) show that the selectivity values of CO 2 /N 2 (15:85) are 57 at 273 K and 121.4 at 295 K, whereas CO 2 /CH 4 (50:50) selectivity values are 8.4 at 273 K and 8.8 at 295 K under 1 bar. The high CO 2 separation selectivity over N 2 and CH 4 makes this MOF a potential candidate for CO 2 separation from flue gas mixture and landfill gas mixture.
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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) | 0.000 | 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 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".