H<sub>2</sub> separation using tubular stainless steel supported natural clinoptilolite membranes
Bibliographic record
Abstract
Abstract Disk membranes generated from high‐purity natural clinoptilolite mineral rock have shown promising hydrogen separation performance. To scale up production of these types of membranes for industrial gas separation, a coating strategy was devised. A mixture of natural clinoptilolite and aluminum silicate was deposited on the inner surface of porous stainless steel tubes by the slip casting technique. Phase composition and morphology of the coating materials were investigated using X‐ray diffraction. The performance was evaluated for a range of gases using single gas permeation tests at different temperatures and pressures. Introduction of the second layer significantly improved the performance of the membrane system. The experiments on the double‐layered membranes measured a hydrogen permeance of 1.65 × 10−7 mol · m−2 · s−1 · Pa−1 at 300 °C. H2/CO2 and H2/C2H6 single gas selectivity was 10.2 and 8.45 respectively at 25 °C and feed pressure of 110 kPa. These results show that natural zeolite coated stainless steel tubular membranes have high potential for large‐scale gas separation at high temperature requirements.
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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".