Batch and fixed‐bed column adsorption of Cu(II), Pb(II) and Cd(II) from aqueous solution onto functionalised SBA‐15 mesoporous silica
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Bibliographic record
Abstract
Abstract Functionalised SBA‐15 mesoporous silica with polyamidoamine groups (PAMAM‐SBA‐15) was successfully prepared with the structure characterised by X‐ray diffraction, nitrogen adsorption–desorption, Fourier transform infrared spectra and thermogravimetric analysis. PAMAM‐SBA‐15 was applied as adsorbent for Cu(II), Pb(II) and Cd(II) ions removal from aqueous solution. The effects of the solution pH, adsorbent dosage and metal ion concentration were studied under the batch mode. The Langmuir model was fitted favourably to the experimental data. The maximum sorptive capacities were determined to be 1.74 mmol g −1 for Cu(II), 1.16 mmol g −1 for Pb(II) and 0.97 mmol g −1 for Cd(II). The overall sorption process was fast and its kinetics was fitted well to a pseudo‐first‐order kinetic model. The mean free energy of sorption, calculated from the Dubinin–Radushkevich isotherm, indicated that the sorption of lead and copper, with E > 16 kJ mol −1 , followed the sorption mechanism by particle diffusion. The adsorbent could be regenerated three times without significant varying its sorption capacity. A series of column tests were performed to determine the breakthrough curves with varying bed heights and flow rates. The breakthrough data gave a good fit to the Thomas model. Maximum sorption capacity of 1.6, 1.3 and 1.0 mmol g −1 were found for Cu(II), Pb(II) and Cd(II), respectively, at flow rate of 0.4 mL min −1 and bed height of 8 cm, which corresponds to 83%, 75% and 73% of metallic ion removal, respectively, which very close to the value determined in the batch process. Bed depth service time model could describe the breakthrough data from the column experiments properly. © 2012 Canadian Society for Chemical Engineering
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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) | 0.001 | 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 it