CoFe<sub>2</sub>O<sub>4</sub>/graphene oxide/ostrich eggshell/chitosan/polypyrrole nanocomposite for removal 4-nitrophenol
Bibliographic record
Abstract
A nanocomposite comprising CoFe2O4/graphene oxide/ostrich eggshell/chitosan/polypyrrole (CF/GO/ES/CS/PPY) was fabricated as both an adsorbent and photocatalyst to examine the adsorption and degradation efficiency of the organic pollutant 4-nitrophenol (4-NP), both in the absence of light and under visible light irradiation. The nanocomposite material outperformed adsorption in photocatalytic experiments conducted using the Box-Behnken Design (BBD) within response surface methodology, which investigated the correlation between responses and process variables and identified optimal combinations with Design Expert software. Under optimal conditions, the highest percentage of adsorption and degradation of 4-NP was achieved, with a pH of 5.04, concentration of 4-NP of 24.73 mg/L, nanocomposite mass of 0.04 g, and time of 27.64 min, resulting in reported efficiencies of 89.76, and 99.98% for adsorption and degradation, respectively. Upon statistical analysis, it is clear that the Langmuir isotherm model is the best fit for the studied phenomena, displaying a strong correlation (0.990) and minimal error. The data suggests that the intraparticle diffusion kinetic model has the highest correlation coefficient (0.9925) among the models examined. The value of ΔG° computed for the adsorption process exhibits an increase from 1.3704 to 3.9439 kJ/mol as the temperature rises, indicating the nonspontaneous nature of the adsorption process.
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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 | 0.000 | 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 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".