Comparison between the performances of <scp>PmPD</scp> ‐ <scp>PVA</scp> membrane synthesized by ammonium persulphate with ferric chloride oxidants used for Congo red dye removal
Bibliographic record
Abstract
Abstract This work focused on investigating the effect of oxidants and their interaction with the monomer (m‐phenylenediamine) (mPD) on performance of the resulting composite membrane. The synthesized poly(m‐phenylenediamine) (PmPD) and poly(vinyl alcohol) (PVA) were deposited onto flat ceramic support made from pozzolan and micronized phosphate. The difference between the two composite membranes is the oxidant used for the chemical polymerization of mPD monomer. The PmPD used to develop the first membrane in this work was synthesized using ammonium persulphate (APS) oxidant. The second membrane was developed in a previous study using ferric chloride (FeCl 3 ) as oxidant. Although PmPD‐based membranes have been explored, few studies have systematically compared the influence of different oxidants on membrane performance, especially for dye removal. This study addresses that gap by evaluating how APS and FeCl 3 affect membrane characteristics and dye rejection efficiency. The effect of oxidants on membrane properties such as microstructure, wettability, permeability, and filtration performances was investigated. The composite membranes were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, energy dispersive X‐ray analysis, and X‐ray diffraction technique. The morphology analysis shows that using APS leads to the formation of uniform microparticles compared to FeCl 3 oxidant. It was proven that the use of APS in the polymerization of the mPD enhances the rejection of the membrane accompanied by with a decrease in permeate flux. It removed up to 99.7% of Congo red under optimal conditions ( Δ P = 3 bar, C = 600, and pH = 4).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".