Application of polyelectrolytes for contaminant removal and recovery during water and wastewater treatment: A critical review
Why this work is in the frame
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Bibliographic record
Abstract
The combination of polymeric characteristics and electrolyte behaviour endow aqueous polyelectrolytes with a strong potential for use in water and wastewater treatment. A correct and effective application of polyelectrolytes or polyelectrolyte complexes can remove different types of contaminants from aqueous solutions efficiently. Polyelectrolytes can be utilized directly as a water treatment material or indirectly as additives or modifiers to improve the effectiveness of existing water treatment processes. Previous reviews on this general research topic focused mainly on the function of polyelectrolytes in coagulation and flocculation processes, but they neglected other potential functions during water treatment processes. The current review introduces the typical polyelectrolytes utilized in water processing, including their properties and their interaction with contaminant species in water, and then summarizes and reviews the various unique applications of polyelectrolytes in water processing, including the polyelectrolyte enhanced ultrafiltration (PEUF) process, the application of polyelectrolytes to efficiently functionalize membranes and adsorbents, and the formation of polyelectrolyte-surfactant aggregates (PSAs) to recover metallic species from water. Finally, the challenges and opportunities for future investigation of the application of polyelectrolytes in water processing and treatment are discussed. • Typical polyelectrolytes utilized in water processing are summarized. • Various unique applications of polyelectrolytes in water processing are reviewed. • PEUF process, modification of membranes and adsorbents, and formation of PSAs to recover metals are emphasized. • The challenges and opportunities for future investigation of the application of polyelectrolytes are discussed.
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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) | 0.001 | 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 | 0.000 | 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 it