Adsorptive performance of sustainable biosorbent from <i>Macadamia integrifoli</i> shell powder for toxic methylene blue dye removal: desirability functions and dye uptake mechanism
Bibliographic record
Abstract
Herein, the potential of Macadamia integrifolia nutshell powder (MSP) as a sustainable, renewable, and cost-effective biosorbent for methylene blue (MB) dye was evaluated. The physicochemical properties of MSP were characterized via XRD, FTIR, FESEM-EDX, and pHpzc analysis. The biosorption process was optimized using the Box-Behnken design (RSM-BBD), to evaluate the influence of MSP dose (0.02–0.1 g/100 mL), contact time (20–300 min), and solution pH (4–10). The desirability function further refined and validated the BBD results, demonstrating that maximum MB removal (98.7%) was achieved at an MSP dose of 0.09 g/100 mL, contact time of 276.1 min, and solution pH of 8.7. Kinetic modeling indicated that MB biosorption onto MSP conformed to the pseudo-second order (PSO) model. The intraparticle diffusion (IPD) model supports a multi-step adsorption process, consisting of surface adsorption, gradual diffusion, and equilibrium stages. The adsorption equilibrium data were well described by the Langmuir and Freundlich isotherm models, confirming a combination of monolayer and multilayer adsorption profiles. The maximum adsorption capacity (qmax) of MSP was estimated to be 128.3 mg/g. The biosorption mechanism was attributed to hydrogen bonding, π-π interactions, electrostatic forces, and pore filling, as evidenced by spectroscopy and bioadsorbent morphology results. The reusability study demonstrated that MSP retained significant adsorption capacity over multiple cycles, highlighting its moderate recyclability. These findings establish MSP as a highly efficient, scalable, and environmentally sustainable bioadsorbent for MB dye removal, offering a practical solution for wastewater treatment applications and options for sustainable water management.
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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 | 0.000 |
| 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 | 0.001 |
| 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".