Cadmium(II) biosorption from aqueous solutions using <i>Hydrilla verticillata</i>
Bibliographic record
Abstract
Abstract The kinetics and equilibrium of cadmium biosorption from aqueous solutions were investigated using fresh tissues of Hydrilla verticillata. The biosorptive characteristics of cadmium ions were studied with respect to well‐established effective parameters, including pH, temperature and contact time. The biosorptive capacity of H. verticillata for cadmium increased with increasing pH. In addition, the resulting isotherms were well‐described by Langmuir and extended Langmuir models (R2 = 0.9794–0.9957 and 0.9880, respectively). The comparison between calculated and experimental qe values showed that the extended Langmuir model had a better simulation for the cadmium biosorption by H. verticillata than the Langmuir isotherm model. The equilibrium biosorption data at a constant temperature were well‐interpreted by the Langmuir model. The maximum biosorptive capacity increased from 33.54 to 37.46 mg/g when the solution temperature was increased from 278 to 298 K. Other various thermodynamic parameters were also estimated. Biosorptive equilibrium was established within approximately 20 min. Moreover, the pseudo‐second‐order equation was more appropriate in predicting biosorptive capacity than the pseudo‐first‐order equation. In practical viewpoints, the abundant and inexpensive plant biomass H. verticillata can be used as an effective and environmentally friendly biosorbent for the detoxification of cadmium from aqueous solutions. © 2012 Canadian Society for Chemical Engineering
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".