Modeling Using the Response Surface Methodology the Activation Process of Moroccan Oil Shale for Removal of Cd (II)
Bibliographic record
Abstract
This study for the first time designed to modeling and optimize of activation process for removal of cadmium (II) ions by adsorption on Moroccan oil shale using the response surface methodology. The optimal activation parameters selection was carried out on the basis of three factors by central composite design (CCD). The factors that have been identified are: activation temperature, activation time and massic ratio (mH2SO4/mYC). The capacity of adsorption of the Cd (II), was chosen as a response. The measured parameters were found in accordance with the predicted values with a coefficient of determination (R2) of 0.92. The model has been confirmed by experimental tests to validate the results obtained. Based on the equation of the model and the desirability function, the activation temperature and activation time significantly effect of the adsorption capacity of Cd (II) ions. According to optimal activation conditions obtained using prediction profiler, the powder of oil shale mixed with H2SO4 at 213.8°C during 30 min in a ratio of 1.76, the adsorption capacity of Cd (II) ions is 68.38 (mg/g), the specific BET surface area of activated oil shale equal to 181.35 (m2/g).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".