Box–Behnken design with desirability function for methylene blue dye adsorption by microporous activated carbon from pomegranate peel using microwave assisted K <sub>2</sub> CO <sub>3</sub> activation
Bibliographic record
Abstract
This research aims to convert pomegranate peel (PP) into microporous activated carbon (PPAC) using a microwave assisted K2CO3 activation method. The optimum activation conditions were carried out with a 1:2 PP/K2CO3 impregnation ratio, radiation power 800 W, and 15 min irradiation time. The statistical Box–Behnken design (BBD) was employed as an effective tool for optimizing the factors that influence the adsorption performance and removal of methylene blue (MB) dye. The output data of BBD with a desirability function indicate a 94.8% removal of 100 mg/L MB at the following experimental conditions: PPAC dose of 0.08 g, solution pH of 7.45, process temperature of 32.1 °C, and a time of 30 min. The pseudo-second order (PSO) kinetic model accounted for the contact time for the adsorption of MB. At equilibrium conditions, the Freundlich adsorption isotherm describes the adsorption results, where the maximum adsorption capacity of PPAC for MB dye was 291.5 mg g−1. This study supports the utilization of biomass waste from pomegranate peels and conversion into renewable and sustainable adsorbent materials. As well, this work contributes to the management of waste biomass and water pollutant sequestration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".