<scp> <i>Eichhornia crassipes</i> </scp> as biosorbent for industrial wastewater treatment: Equilibrium and kinetic studies
Bibliographic record
Abstract
Abstract Adsorption is an economical and widely used technique for removing dye from wastewater, especially for non‐biodegradable pollutants. In this study, the effectiveness of water hyacinth (WH) as an adsorbent for the removal of methylene blue (MB) was conducted in a batch process. Scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) were used to characterize WH. The influence of operational parameters such as dye concentration, pH, WH dose, and contact time was studied to determine the most favourable experimental conditions. Dubinin Radushkevich, Freundlich, Langmuir, and Temkin isotherms were used to fit the equilibrium data for mechanistic understating of the adsorption process. It was found that Freundlich isotherm had the best fit for equilibrium adsorption data with the highest correlation coefficient value (R 2 = 0.996). The kinetic data of adsorption showed R 2 = 0.99, following the pseudo‐second‐order model for a dye concentration of 50–200 mg L −1 . The results also showed that the maximum removal was obtained at pH of 8, dye concentration of 200 mg L −1 , with an equilibrium time of 90 min, and an adsorbent dose of 3 g L −1 . The Temkin isotherm equilibrium binding constant ( A T ) = 11.00 L g −1 and heat of adsorption of 53.08 J mol −1 suggest physical adsorption. The investigation uncovered WH as a productive and efficient adsorbent for the expulsion of MB 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 | 0.000 | 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) | 0.000 | 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".