Assessment and optimization of total ammonia nitrogen adsorption in aqueous phase by sodium functionalized graphene oxide using response surface methodology
Bibliographic record
Abstract
Abstract Total ammonia nitrogen (TAN) uptake by sodium functionalized graphene oxide as an efficient adsorbent was evaluated and optimized using response surface methodology (RSM). Batch adsorption tests were carried out based on a central composite design experimental plan at 3 pH levels (6, 7, and 8) and 3 temperature levels (5, 25, and 45°C). The equilibrium condition was reached within 5 min. Quadratic models for percent TAN removal ( R %) and solid phase TAN concentration ( q e ) as response were obtained and evaluated by statistical analysis to predict the experimental data. The models were reduced by eliminating insignificant terms. The final reduced models were significant ( p < .0001) with R 2 values .96 for R % and .97 for q e , respectively. The optimum pH and temperature to reach the maximum values for R % (58.23%) and q e (27.45 mg/g) were predicted by the RSM. The laboratory experiments were in very good agreement with the predicted optimized values for R % and q e by RMS as the error was 1.2 and 0.3%, respectively.
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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 | 0.001 | 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) | 0.002 | 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".