Modified Poly(ethylene terephthalate) Nano Fibers for Removal of Copper(II) Ions
Bibliographic record
Abstract
In this research, the adsorption of Cu2+ ions from aqueous solution was investigated by the modified poly (ethylene terephthalate) fibers as a new adsorbent. The best condition of electrospinning was recorded (voltage= 10 kV- distance from nozzle= 12.5 cm - solution convcentration= 0.2 g/mL). The optimum condition for removal of Cu2+ ions were determined (pH=10 - time= 60 min - C= 120 mg/L, qm = 62.4 mg/g). The adsorption data were best fitted by dubinin-radushkevich isotherm and pseudo-second order kinetic models, as well. Structure of the nanofibers were emphasized by scanning electron microscpy (SEM) and thermo gravimetric analysis (TGA).
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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) | 0.000 | 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 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".