Sulphonated date palm ( <i>Phoenix dactylifera</i> ) stone <i>via</i> microwave‑assisted H <sub>2</sub> SO <sub>4</sub> activation: optimisation with desirability function for methylene blue adsorption
Bibliographic record
Abstract
In this work, a sulphonated date palm (Phoenix dactylifera) stone (SDPS) was produced as a cost-effective and renewable adsorbent for the removal of a cationic dye called methylene blue (MB). The production process involved the use of microwave irradiation combined with H2SO4 activation under the condition of 600 W microwave radiation for 15 min. The physicochemical characteristics of SDPS were evaluated using various analytical techniques, including XRD, BET, FTIR, pHpzc, and SEM. The Box-Behnken design (BBD) was employed to optimise key adsorption variables, including A: SDPS dosage (0.02–0.1 g/100 mL), B: pH (4–10), and C: contact time (5–25) min. According to the BBD model, the most effective removal of MB (98.4%) occurred with a dosage of 0.06 g/100 mL of SDPS, a pH of 10, and a contact time of 25 min. The rate of adsorption of the MB dye followed a pseudo second order (PSO) model, whereas the equilibrium adsorption was described by the Langmuir and Temkin models. The maximum adsorption capacity (qmax) of SDPS for MB dye was found to be 122.3 mg/g at 25°C. Several contributions to the MB dye adsorption process include electrostatic interactions, H-bonding, pore filling, and π-π stacking onto the SDPS adsorbent surface.
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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".