Hydrogen-sieving zeolitic films by coating zeolite nanosheets on porous polymeric support
Bibliographic record
Abstract
The synthesis of high-performance gas-sieving zeolitic film is challenging because it involves seeded secondary growth which is complex and difficult to reproduce. Additionally, expensive asymmetric inorganic porous supports are often needed for calcination of the zeolite films. Herein, scalable preparation of H2-sieving RUB-15 nanosheet films is reported bypassing the need for secondary growth and expensive supports. A novel, low-cost, thermally-robust, porous polybenzimidazole copolymer (PBI-AM Fumion®) support is prepared which allows deposition of thin, compact, and oriented RUB-15 nanosheets films without cracks or pinhole defects. The film hosts two transport pathways, H2-sieving six-membered silicate rings in the nanosheets and nonselective intersheet gaps maintained by the organic guest species in the gallery spacing. The latter is eliminated by a low-temperature (330 °C) calcination where the crystalline order in the nanosheets is preserved. The resulting zeolitic films yielded H2 permeances of 100–400 GPU and H2/CO2 selectivities above 20 at temperatures above 200 °C. The facile and scalable fabrication procedure with an attractive H2-sieving performance at elevated temperatures make these membranes promising for pre-combustion carbon capture.
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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 | 0.001 |
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".