New Concept for Dual-Layer Hydrophilic/Hydrophobic Composite Membrane for Membrane Distillation
Bibliographic record
Abstract
This study presents a new concept of a simple method for the synthesis of dual layer hydrophilic/hydrophobic composite membranes for membrane distillation (MD). The membranes were prepared of poly(vinylidenefluoride) (PVDF) by phase inversion. The synthesis was realized by allowing a full or partial penetration of the polymer solution through one or two non-woven support (NWS) layers. This was achieved by proper selection of a thin NWS having high stiffness, high porosity and low surface tension, in combination with a runny polymer solution and sufficient time gap between casting and coagulation. The applied preparation method was effective in yielding dual layer composite membranes. The first layer atop the NWS was a hydrophilic or slightly hydrophobic one (contact angle (CA) of 88-92º), while the bottom layer beneath the NWS was highly hydrophobic (CA=132-140º). The difference in surface energy between the top and bottom layers originated from a difference in morphology. A smooth and dense top layer is formed as a result of an instantaneous demixing, while a porous and multi-scale network with some degrees of spherulitical structure was formed on the bottom by a delayed demixing mechanism. Direct contact MD (DCMD) results showed that the obtained flux was comparable to other composite MD membranes with high salt rejection. Membrane alignment inside the MD module is a critical element in determining the membrane performance and is shown to significantly increase flux when a top facing feed configuration is used.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".