Nanofiltration and Reverse Osmosis for Reuse of Indigo Dye Rinsing Waters
Why this work is in the frame
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Bibliographic record
Abstract
A membrane based treatment strategy was developed for the possible recycling of rinsing wastewater from indigo dyeing to the process itself. Performances of three different nanofiltration (NF) (NF 270 and NF 90, Dow Film Tech, USA and NF 99, Alfa Laval, Denmark) and two different reverse osmosis (RO) (HR 98 PP and CA 995 PE, Alfa Laval, Denmark) membranes were investigated with wastewater collected from the first post-rinsing tank of indigo dyeing process of a denim manufacturing plant. Dead-end microfiltration with a 5 µm filter was employed to remove coarse particles and minimize fouling of further NF and RO membranes. For NF and RO, a lab scale plate-and-frame membrane module was operated at a pressure of 5.07 bar and at a 0.62 m/s cross-flow velocity. The permeate quality from all the tested NF and RO membranes was acceptable for reuse in terms of COD and color. However, only the permeate from HR 98 PP RO and NF 90 membranes were with an acceptable conductivity. On the other hand, NF 270 membrane was superior to all the other NF and RO membranes in terms of the permeation rate. Flux declines obtained for all membranes were higher than 50% but fouling was not considerable and completely reversible. The good performance of NF 270 in terms of permeate quality (permeate conductivity, color, and COD values were 4.3 mS/cm, 8 Pt-Co, and 87 mg/L, respectively) together with a higher flux makes this membrane preferable over the other membranes to recycle denim textile rinsing wastewaters.
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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 | 0.001 | 0.001 |
| 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 | 0.002 |
| 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 | 0.000 |
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