Chemically crosslinked electrospun chitosan/poly (vinyl alcohol) membranes with encapsulated zeolite for organic dye removal
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
Safe water is a basic human right, yet about 25 % of the global population lacks reliable access. Rapid urbanization and industrialization, especially in developing countries, have worsened water pollution, causing environmental and health issues. To achieve global safe water goals, affordable and effective wastewater treatment solutions are needed. To this end, zeolites are highly effective for wastewater treatment due to their unique adsorption properties; however, their efficacy can be significantly hindered due to a propensity to aggregate. Herein, electrospun chitosan (CS)/polyvinyl alcohol (PVA) membranes are fabricated to encapsulate sodium Y (NaY) zeolites, preventing their unwanted aggregation. By utilizing 1,1’-Carbonyldiimidazole (CDI) as a green crosslinker, NaY could be effectively immobilized within the electrospun membranes. CDI crosslinking enhanced the mechanical properties of the composite membranes, with improved Young's Modulus, ultimate tensile stress, and toughness as compared to non-crosslinked membranes. After optimizing the electrospinning process and formulation, as a proof of concept membrane modules were prepared and tested for the filtration of methylene blue (MB) as a model organic dye. Continuous filtration tests showed effective MB removal, achieving a 95 % removal rate and 287 LMH flux at an initial MB concentration of 50 mg/L, using a 1 g/L adsorbent dosage. Crucially, these membranes showed good mechanical stability and potential to be regenerated/recycled, yielding only a 13 % decrease in performance after five adsorption/desorption cycles. We anticipate that this approach could lead to the development of functional membranes for removing organic dyes and other emerging contaminants from water, directly improving access to safe, clean water.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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