A Review of Temperature Effects on Membrane Filtration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Membrane technology plays a vital role in drinking water and wastewater treatments. Among a number of factors affecting membrane performance, temperature is one of the dominant factors determining membrane performance. In this review, the impact of temperature on membrane structure, fouling, chemical cleaning, and membrane performance is reviewed and discussed with a particular focus on cold temperature effects. The findings from the literature suggest that cold temperatures have detrimental impacts on membrane structure, fouling, and chemical cleaning, and thus could negatively affect membrane filtration operations and performance, while warm and hot temperatures might expand membrane pores, increase membrane flux, improve membrane chemical cleaning efficiency, and interfere with biological processes in membrane bioreactors. The research gaps, challenges, and directions of temperature effects are identified and discussed indepth. Future studies focusing on the impact of temperature on membrane processes used in water and wastewater treatment and the development of methods that could reduce the adverse effect of temperature on membrane operations are needed.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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 it