Chromium(VI) removal from aqueous solution using a new synthesized adsorbent
Bibliographic record
Abstract
In order to effectively utilize agricultural wastes, the feasibility of using a novel calcined composite of dolomite, montmorillonite, and corn stover for removing chromium(VI) from aqueous solutions was examined. Batch experiments were conducted to investigate the effect of composite dosage, solution pH, initial concentration of chromium(VI), and temperature during the removal process. Chromium(VI) removal efficiency increased with increase in amount of the composite but remained almost unchanged (84–86%) when the solution pH increased from 2.0 to 11.0. The increase in chromium(VI) removal efficiency with increase in temperature from 20 to 40°C indicated that high temperature favored the removal process. This conclusion was also confirmed by adsorption energy evaluation where the reaction process was found to be endothermic and spontaneous. The removal process well fitted the pseudo-second-order kinetic model. Fitting of the experimental results with the intraparticle diffusion model revealed that the adsorption process was not controlled by the intraparticle diffusion. Isotherm studies demonstrated that the homogeneity of the composite surface and physical forces may more significantly affect the removal process.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".