Reactive adsorption of Safranin O: surface – pore diffusion modeling and degradation study
Bibliographic record
Abstract
Abstract Granular activated carbon was doped with iron (Fe-AC) and was used to study the removal of Safranin O (SO) using the Fe-AC/H2O2 system for reactive adsorption and Fe-AC for adsorption. Fe-AC and H2O2 doses were optimized to obtain maximum removal of SO. Maximum removal was found to be 96.1% after 5 h using 1.0 g/L Fe-AC and 5.0 mM hydrogen peroxide doses for 10 mg/L initial SO concentration. Kinetic study suggested the suitability of the pseudo-first-order model for reactive adsorption. The Langmuir isotherm explained well the sorption of SO onto Fe-AC. Parallel-pore-reactive adsorption model was applied and validated. By fitting the experimental data to the model, it is observed that the surface reaction rate coefficient, kr, was found to be five times that of the apparent rate constant, kapp. Parameters such as the external liquid film mass transfer coefficient, macro-pore and micro-pore diffusivities were estimated by regression analysis. Pore diffusion and surface reaction were found to be rate controlling for adsorption and reactive adsorption, respectively. An oxidative degradation of SO took place via hydroxylation and ring cleavage processes.
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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) | 0.000 | 0.001 |
| 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 | 0.001 | 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".