Fabrication and characterization of affordable hydrophobic ceramic hollow fibre membrane for contacting processes
Bibliographic record
Abstract
Affordable hydrophobic hollow fibre membranes were prepared using kaolin and alumina based ceramic powders via a combined phase inversion and sintering technique, followed by a grafting with fluoroalkylsilane (FAS). The crux of the matter in this paper is to study the changes in the properties of the hollow fibre membranes (gas permeation, mechanical strength, pore size, porosity, tortuosity, morphology, and contact angle) by the addition of alumina (Al2O3) to the pure kaolin with mono or multiparticle sizes. By varying the overall loading and particle size of alumina addition, different morphologies of the membranes were obtained due to the differences in the path lengths during phase inversion process for each solvent and nonsolvent exchange. The successful grafting with FAS was evidenced by the increase in contact angle from nearly equal to zero degree before grafting to 140° after grafting. Kaolin–alumina-4, one of the hollow fibres fabricated in this work, achieved a mean pore size of 0.25 μm with the bending strength of 96.4 MPa and high nitrogen permeance of 2.3×10-5 mol·m-2·Pa-1·s-1, which makes the hollow fibre most suitable for the membrane contactor application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".