Thermal Carbonization of Biomass Wood Dust and Algae Wastes <i>via</i> Microwave-Assisted H<sub>3</sub>PO<sub>4</sub>: Desirability Function and Statistical Optimization for Methylene Blue Dye Removal
Bibliographic record
Abstract
This research utilized a carbonization procedure via microwave irradiation assisted by H3PO4 to generate a cost-effective adsorbent (CWDAG) from wood dust (WD) and algal (AG) biomass. The resulting CWDAG adsorbent was characterized for its methylene blue (MB) dye adsorption properties. The activation process employs 800 W microwave radiation for 15 min under a nitrogen gas (99.99%) atmosphere. Multiple techniques were employed to study the physicochemical properties of CWDAG, such as FTIR, XRD, FSEM-EDX, pHpzc, and BET. Box-Behnken design (BBD) was employed to optimize the three important parameters of adsorption, as follows: A: CWDAG dosage (0.02–0.12 g), B: pH (4–10), and C: contact time (30–420) min. BBD results show the highest removal of MB (98.6%) was met with a contact period of 225 min, a dosage of 0.12 g/100 mL of CWDAG at pH 10. Analysis of the kinetic profiles show that MB adsorption onto CWDAG occurred via a pseudo-second order (PSO) model. Adsorption isotherm analysis at equilibrium confirm that the Freundlich and Langmuir isotherm models fit the equilibrium data with similar goodness-of-fit results. Based on the Langmuir model, the maximum adsorption capacity (qmax) of CWDAG for MB is 32.3 mg/g. The possible mechanism of MB adsorption on the CWDAG surface include several contributions such as π–π stacking, H-bonding electrostatic forces, and pore filling.
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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".