Adsorption of Basic Yellow 28 onto chemically‐modified activated carbon: Characterization and adsorption mechanisms
Bibliographic record
Abstract
Abstract Adsorption processes have been investigated and successfully applied in the removal of dyes from textile plant wastewaters. Activated carbon is one of the most commonly used adsorbents, due to its excellent characteristics and relatively low cost. However, its dye removal efficiency depends on several parameters, notably the chemical nature of the carbon surface. To enhance the adsorption capacity, different methods have been proposed in the literature, chemical modification using acidic agents being one of the most commonly used. In this study, the performance of samples of activated carbon chemically modified with nitric and phosphoric acid in the adsorption of Basic Yellow 28 is evaluated. The physical and chemical structure of these adsorbents was investigated using electron microscopy, X‐ray spectrometry, and infrared spectroscopy, revealing significant modifications depending on the agent used. Adsorption tests were conducted at three different temperatures and the adsorption kinetics and isotherms were evaluated. Comparing the experimental data and results obtained with models reported in the literature showed that in both cases the pseudo‐second order kinetics model and the Freundlich isotherms provided the closest fits. The samples modified with nitric acid presented better overall performance, particularly due to pore collapse observed for the samples treated with phosphoric acid, which caused a significant reduction in the surface area and total pore volume. These results indicate that the chemically‐modified activated carbon can be employed in the removal of basic dyes from textile effluents, allowing the reuse of the effluent.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".