Development of polyimide membranes for the separation of water vapor from organic compounds
Bibliographic record
Abstract
Abstract Attempts were made to develop solvent‐resistant polyimide capillary membranes with integrally skinned asymmetric structure to be used for the treatment of wood dryer emissions or vacuum pyrolysis aqueous effluents. Model mixtures of 1‐propanol (1‐PrOH)/H2O and acetic acid (AA)/ H2O, with concentrations of 10–90 wt % of organic components, were used as vaporous feeds. Solvent‐resistant membranes with good mechanical and excellent vapor separation properties were prepared from polyimides based on PMDA and BPDA by the dry/wet phase‐inversion technique. Molecular structure largely influences membrane properties. For the asymmetric polyimide membranes studied, a tendency similar to that of homogeneous dense membrane was found. Membranes prepared from polyimides with diamine and dianhydride moieties, both containing rigid backbone and aromatic rings, displayed higher permeability and selectivity. Test conditions exhibited influences on membrane separation performance. Membranes prepared from copolyimide BPDA–50DDS/50ODA and PMDA–50DDS/50ODA exhibited the best mechanical and chemical properties as well as water vapor separation properties, which are considered to be of practical usefulness for applications of these membranes in the removal of water from water/organic mixtures. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 139–152, 2002
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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) | 0.001 | 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 | 0.001 |
| 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".