Preparation and Performance of PAN–PAC Nanofibers by Electrospinning Process to Remove NOM from Water
Bibliographic record
Abstract
The technology based on electrospun membranes exhibits great potential in water treatment. This study presents experimental data involving the fabrication of nanofiber membranes with powdered activated carbon (PAC) and its application for the removal of natural organic matter. The fabricated membrane materials were characterized using various techniques. These include scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction analysis. The incorporation of PAC nanoparticles influences the structure and physicochemical properties as well as the transport and separation characteristics of the produced membranes. The applicability of the fabricated carbon-based membrane was tested in the filtration experiments. The fabricated membrane is characterized by a high NOM removal efficiency of 79% in the filtration process. Further modification of the membrane composition may result in a further increase in the efficiency of removing contaminants from water.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".