Optimization of nickel ions removal from aqueous solutions by chitosan-polyethylene oxide electrospun nanofibers
Bibliographic record
Abstract
Chitosan-polyethylene oxide (Cs/PEO) electrospun nanofibers were prepared by electrospinning process in order to remove nickel ions from aqueous solutions by a chelation mechanism. Response surface methodology (RSM) was used to optimize adsorption efficiency of nickel ions on Cs/PEO nanofibers. The combined effects of adsorption operating parameters, namely, the adsorbent dose, initial nickel ions concentration, temperature, and NaCl concentration, on adsorption efficiency were investigated using a central composite face-centered (CCF) design. Results showed that an optimal adsorption capacity of 64.4% was obtained under the following conditions: 75 mg of adsorbent dose, initial nickel concentration of 100 ppm, a temperature of 75C, and a 1M NaCl concentration.
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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 | 0.001 |
| 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".