Unexpectedly Strong Size-Sieving Ability in Carbonized Polybenzimidazole for Membrane H<sub>2</sub>/CO<sub>2</sub> Separation
Bibliographic record
Abstract
Polymers with high permeability and strong size-sieving ability are needed for H 2 /CO 2 separation at temperatures ranging from 100 to 300 °C to enable an energy-efficient precombustion CO 2 capture process. However, such polymers usually suffer from a permeability/selectivity tradeoff, that is, polymers with high permeability tend to exhibit a weak size-sieving ability and thus low selectivity. Herein, we demonstrate that carbonization of a suitable polymer precursor (i.e., polybenzimidazole or PBI) generates microcavities (leading to high H 2 permeability) and ultramicroporous channels (leading to strong size-sieving ability and thus high H 2 /CO 2 selectivity). Specifically, carbonization of PBI at 900 °C (CMS@900) doubles H 2 permeability and increases H 2 /CO 2 selectivity from 14 to 80 at 150 °C. When tested with simulated syngas-containing equimolar H 2 and CO 2 in the presence of water vapor for 120 h, CMS@900 exhibits stable H 2 permeability of ≈36 barrer and H 2 /CO 2 selectivity of ≈53 at 150 °C, above Robeson’s 2008 upper bound and demonstrating robustness against physical aging and CO 2 plasticization.
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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 | 0.000 |
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".