Food-grade algae modified Schiff base-chitosan benzaldehyde composite for cationic methyl violet 2B dye removal: RSM statistical parametric optimization
Bibliographic record
Abstract
This work aims to apply the use of food-grade algae (FGA) composited with chitosan-benzaldehyde Schiff base biopolymer (CHA-BD) as a new adsorbent (CHA-BA/FGA) for methyl violet 2B (MV 2B) dye removal from aqueous solutions. The effect of three processing variables, including CHA-BA/FGA dosage (0.02-0.1 g/100 mL), pH solution (4-10), and contact duration (10-120 min) on the removal of MV 2B was investigated using the Box-Behnken design (BBD) model. Kinetic and equilibrium dye adsorption profiles reveal that the uptake of MV 2B dye by CHA-BA/FGA is described by the pseudo-second kinetics and the Langmuir models. The thermodynamics of the adsorption process (ΔG°, ΔH°, and ΔS°) reveal spontaneous and favorable adsorption parameters of MV 2B dye onto the CHA-BA/FGA biocomposite at ambient conditions. The CHA-BA/FGA exhibited the maximum ability to absorb MV 2B of 126.51 mg/g (operating conditions: CHA-BA/FGA dose = 0.09 g/100 mL, solution pH = 8.68, and temperature = 25 °C). Various interactions, including H-bonding, electrostatic forces, π-π stacking, and n-π stacking provide an account of the hypothesized mechanism of MV 2B adsorption onto the surface of CHA-BA/FGA. This research reveals that CHA-BA/FGA with its unique biocomposite structure and favorable adsorption properties can be used to remove harmful cationic dyes from 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".