Novel Technology for the Removal of Brilliant Green from Water: Influence of Post-Oxidation, Environmental Conditions, and Capping
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Chemical dyes are used in a wide range of anthropogenic activities and are generally not biodegradable. Hence, sustainable recycling processes are needed to avoid their accumulation in the environment. A one-step synthesis of Fe core –maghemite shell (Fe–MM) for facile, instantaneous, cost-effective, sustainable, and efficient removal of brilliant green (BG) dye from water has been reported here. The homogenous and monolayer type of adsorption is, to our knowledge, the most efficient, with a maximum uptake capacity of 1000 mg·g –1, for BG on Fe–MM. This adsorbent was shown to be efficient in occurring in time-scales of seconds and to be readily recyclable (ca. 91%). As iron/iron oxide possesses magnetic behavior, a strong magnet could be used to separate Fe–MM coated with BG. Thus, the recycling process required a minimum amount of energy. Capping Fe–MM by hydrophilic clay minerals further enhanced the BG uptake capacity, by reducing unwanted aggregation. Interestingly, capping the adsorbent by hydrophobic plastic (low-density polyethylene) had a completely inverse effect on clay minerals. BG removal using this method is found to be quite selective among the five common industrial dyes tested in this study. To shed light on the life cycle analysis of the composite in the environment, the influence of selected physicochemical factors ( T, pH, h ν, O 3, and NO 2 ) was examined, along with four types of water samples (melted snow, rain, river, and tap water). To evaluate the potential limitations of this technique, because of likely competitive reactions with metal ion contaminants in aquatic systems, additional experiments with 13 metal ions were performed. To decipher the adsorption mechanism, we deployed four reducing agents (NaBH 4, hydrazine, LiAlH 4, and polyphenols in green tea) and NaBH 4, exclusively, favored the generation of an efficient adsorbent via aerial oxidation. The drift of electron density from electron-rich Fe core to maghemite shells was attributed to be responsible for the electrostatic adsorption of N + in BG toward Fe–MM. This technology is deemed to be environmentally sustainable in environmental remediation, namely, in waste management protocol.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".