Applying MCM-48 mesoporous material, equilibrium, isotherm, and mechanism for the effective adsorption of 4-nitroaniline from wastewater
Bibliographic record
Abstract
Abstract In this work, the MCM-48 mesoporous material was prepared and characterized to apply it as an active adsorbent for the adsorption of 4-nitroaniline (4-Nitrobenzenamine) from wastewater. The MCM-48 characterizations were specified by implementing various techniques such as; scanning electron microscopy (SEM), Energy dispersive X-ray analysis (EDAX), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) surface area, pore size distribution (PSD), and Fourier transform infrared (FTIR). The batch adsorption results showed that the MCM-48 was very active for the 4-nitroaniline adsorption from wastewater. The adsorption equilibrium results were analyzed by applying isotherms like Langmuir, Freundlich, and Temkin. The maximum experimental uptake according to type I Langmuir adsorption was found to be 90 mg g −1 approximately. The Langmuir model with determination coefficient R 2 = 0.9965 is superior than the Freundlich model R 2 = 0.99628 and Temkin model R 2 = 0.9834. The kinetic adsorption was investigated according to pseudo 1st order, pseudo 2nd order, and Intraparticle diffusion model. The kinetic results demonstrated that the regression coefficients are so high R 2 = 0.9949, that mean the pseudo 2nd order hypothesis for the adsorption mechanism process appears to be well-supported. The findings of adsorption isotherms and kinetics studies indicate the adsorption mechanism is a chemisorption and physical adsorption process.
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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) | 0.001 | 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 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".