Efficient separation of butane isomers via ZIF-8 slurry on laboratory- and pilot-scale
Bibliographic record
Abstract
n-butane and isobutane are important petrochemical raw materials. Their separation is challenging because of their similar properties, including boiling point. Here, we report a zeolitic imidazolate framework-8 (ZIF-8)/N,N-Dimethylpropyleneurea (DMPU)-water slurry as sorption material to separate butane mixtures. The isobutane/n-butane selectivity of ZIF-8/DMPU-water slurries is as high as 890 with high kinetic performance, which transcends the upper limit of various separation materials or membranes reported in the literature. More encouragingly, a continuous pilot separation device was established, and the test results show that the purity and recovery ratio of isobutane product are 99.46 mol% and 87%, respectively, which are superior to the corresponding performance (98.56 mol% and 54%) of the industrial distillation tower. To the best of our knowledge, the use of metal-organic frameworks (MOFs) for gas separation in pilot scale remains underexplored, and thus this work provides a step forward to the commercial application of MOFs in gas separation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".