ZIF‐based water‐stable mixed‐matrix membranes for effective CO<sub>2</sub> separation from humid flue gas
Bibliographic record
Abstract
Abstract Water stable mixed‐matrix membranes (MMMs) were developed to help control global warming by capturing and sequestrating carbon dioxide (CO2) from humid flue gas originated from burning of fossil fuels. MMMs of different compositions were prepared by doping glassy polymer Ultrason® S 6010 (US) with nanocrystals of zeolitic imidazolate frameworks (ZIF‐302) in varying degrees. A solution‐casting technique was used to fabricate various MMMs to optimize their CO2 capturing performance from both dry and wet gases. The prepared composite membranes indicated enhanced filler‐polymer interfacial adhesion, consistent distribution of nanofiller, and thermally stable matrix configuration. CO2 permeability of the membranes was enhanced as demonstrated by gas sorption and single gas permeation tests carried out under dry and moist circumstances. As compared to neat Ultrason® membrane, CO2 permeability and expected CO2/N2 permselectivity of the mixed membrane doped with 40 g/g ZIF‐302 nanocrystals were significantly enhanced. In contrast to the majority of previously reported membranes, key features of fabricated MMMs include their structural stability under humid conditions coupled with better and unaffected gas separation performance.
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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".