Simple and green technique for sequestration and concentration of silver nanoparticles by polysaccharides immobilized on glass beads in aqueous media
Bibliographic record
Abstract
BACKGROUND: Engineered nanoparticles have unique properties compared to bulk materials and their commercial uses growing rapidly. They represent a potential risk for environment and health and could be eventually released in water. Silver nanoparticles (Ag NP) are applied in various products and are well-known for their antibacterial properties. Nowadays, pre-concentration and separation methods for Ag NP possess some limitations. Here, we present a simple, green method to sequestrate and concentrate Ag NP from different aqueous media. RESULTS: Supported polysaccharides on glass beads synthesized in water by a single step reaction show high sequestration capacity of citrate-coated Ag NP in aqueous media. Supported polysaccharides were characterized by infrared spectroscopy, scanning electron microscopy (SEM) and elemental analysis. Sequestration of 83.0 % of Ag NP was attained from a 20 μg.L(-1) aqueous solution with supported chitosan in water whereas supported 2-hydroxyethylcellulose (HEC) reached 64.0 % in synthetic seawater in 2 h. The influence of polymer/glass beads ratio and molecular weight of polysaccharides was also studied. The effect of the salinity and humic acids on sequestration of Ag NP was investigated. Supported polymers have shown high performance for sequestration of ionic silver. Sequestration of 82.5 % and 80.8 % were obtained from a 60 μg.L(-1) silver ion (as nitrate salt) with supported HEC and chitosan, respectively. Sequestrated Ag NP was characterized with transmission electron microscopy (TEM) where images showed Ag NP with unchanged size and shape. CONCLUSIONS: This sequestration method, involving green synthesis, allows efficient concentration and characterization of Ag NP from different aqueous media. This simple and fast method is a potential sustainable technique for elimination of Ag NP and ionic silver from waste waters and waters at different salinities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".