Response surface methodology for optimizing methylene blue dye removal by mesoporous activated carbon derived from renewable woody <i>Bambusoideae</i> waste
Bibliographic record
Abstract
activation. The potential application of BBAC as an effective adsorbent for the removal of methylene blue (MB) dye from aqueous solutions was investigated. Response surface methodology (RSM) was employed to evaluate key adsorption characteristics, which included BBAC dosage (A: 0.02-0.08 g/L), pH (B: 4-10), and time (C: 2-8 min). The adsorption isotherm analysis revealed that the adsorption of MB followed the Freundlich model. Moreover, the kinetic data were well-described by the pseudo-second-order model, suggesting the role of a chemisorption process. The BBAC demonstrated a notable MB adsorption capacity of 195.8 mg/g, highlighting its effectiveness as an adsorbent. Multiple mechanisms were identified as controlling factors in MB adsorption by BBAC, including electrostatic forces, π-π stacking, and H-bonding interactions. The findings of this study indicate that BBAC derived from bamboo has the potential to be a promising adsorbent for the treatment of wastewater containing organic dyes. The employment of sustainable precursors like bamboo for activated carbon production contributes to environmentally friendly waste management practices and offers a solution for the remediation of dye-contaminated wastewater.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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 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".