Adsorption Study of Methylene Blue from Aqueous Solutions onto Bituminous Coal Based Activated Carbon
Bibliographic record
Abstract
Adsorption of methylene blue (MB) on activated carbon developed from bituminous coal (Barapukuria Coal) by physical activation has been investigated. The impacts of numerous variables, including absorbent concentration, contact time, initial dye concentration, and temperature, were explored. The equilibrium adsorption data analysis was performed using the Freundlich, Langmuir, and Temkin adsorption models. The Langmuir isotherm was considered to be the most appropriate. The Langmuir adsorption capacities (Qo) in 298, 303, 308, 313, 323, and 333K are 80.65, 84.75, 87.72, 90.09, 91.74, and 92.59 mg g-1, respectively. The dye removal percentages at 60 °C decline from 99.84% to 79.38% when dye concentrations are increased from 100 to 350 mgL-1. Increases in adsorbent concentration result in enhanced methylene blue adsorption because of increases in surface area and the number of active centers. From the thermodynamic studies, negative adsorption free energy (ΔG°) implies spontaneous adsorption, while positive enthalpy (ΔH°) reflects endothermic adsorption. Journal of Engineering Science 13(2), 2022, 91-100
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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 | 0.000 | 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 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".