Transport in reverse osmosis membranes: observations and comments on the pore flow model versus the solution‒diffusion model
Bibliographic record
Abstract
Sixty-four years have passed since the announcement of the cellulose acetate membrane for seawater desalination by Loeb and Sourirajan at UCLA on 23 Aug 1960. Reverse osmosis (RO) is now well established as a process for desalination of seawater, brackish water, as well as for wastewater treatment. The number of research papers on RO is growing. In contrast to the numerous publications on RO membrane preparation and applications, studies on transport mechanisms have been largely neglected. However, this changed recently when M. Elimelech’s research group from Yale University published several papers challenging the applicability of the solution‒diffusion (S‒D) model. Especially, in the most recent paper published in 2024, they have shown seven reasons why the well-accepted S‒D model appears to be wrong. It is interesting to note that, according to Srinivasa Sourirajan, one of the co-inventors of cellulose acetate RO membrane, their work was guided by the Preferential Sorption‒Capillary Flow model. Moreover, he wrote that this pore model was based on the presence of a pure water layer at the salt solution‒air interface, which could be predicted by the Gibbs Adsorption Isotherm. The purpose of this short communication is to present some observations and discussion in response to the 2024 paper published by Elimelech’s group in Desalination journal. In addition, the Gibbs Adsorption Isotherm was revisited to examine if there is a pure water layer at the sodium chloride‒cellulose acetate membrane interface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".