Comprehensive Characterization of Commercial Reverse Osmosis Membranes through High-Temperature Cross-Flow Filtration
Bibliographic record
Abstract
Developing thermally stable reverse osmosis membranes is a potential game-changer in high-temperature water treatment. In this work, the performance of three commercial reverse osmosis membranes was evaluated with a series of high-temperature filtrations. The membranes were tested with different filtration methodologies: long-term operation, cyclic tests, controlled stepwise temperature increment, and permeability tests. The morphological and physiochemical characterizations were performed to study the impact of high-temperature filtration on the membranes' chemical composition and morphological characteristics. An increase in the temperature deteriorated the membrane performance in terms of water flux and salt rejection. Flux decline at high temperatures was recognized as the primary concern for high-temperature filtrations, restricting the applications of commercial membranes for long-term operations. This research provides valuable insights for researchers aiming to thoroughly characterize reverse osmosis membranes at high temperatures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".