Adsorption of reduced chromium(<scp>VI</scp>) ions by vitamin C tablets onto a tellurato‐functionalized cellulose derivative and its composite with <i>Cyanobacteria</i> green algae in aqueous media
Bibliographic record
Abstract
Abstract The removal of toxic chromium(VI) ions from wastewaters in the environment are of considerable importance throughout the world as these ions are known to cause severe medical problems in living organisms. This article describes a novel reduction process for Cr(VI) ions to the less toxic Cr(III) ions in typical wastewaters by using ecofriendly vitamin C tablets as a source of ascorbic acid, which completely reduces Cr(VI) to Cr(III) ions. The efficient adsorption of reduced Cr(VI) ions onto cellulose functionalized with sodium‐tellurate, Cell‐TeO(OH) 4 (ONa)/Cell‐Cl {Cell‐Te} , both in the absence and the presence of Cyanobacteria green algae (CBGA), has been accomplished. This green algae has polysaccharide binding groups that enhance the adsorption of heavy metal ions. The uptake of reduced Cr(VI) ions by the two sorbents are dependent on the initial pH, contact time, temperature, presence of foreign ions, sorbent dose, and initial Cr(VI) ion concentration. The maximum uptakes of reduced Cr(VI) ions by {Cell‐Te} and Cell‐TeO(OH) 4 (ONa)/Cell‐Cl:CBGA; 3:2 w/w {Cell‐Te‐CBGA} are 56.5 and 88.7 mg g −1 , respectively. The hydroxyl and amide groups on the surface of the CBGA most probably play a significant role in facilitating the adsorption capacities of the two sorbents toward Cr(VI) ions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".