Hybrid Beads of Zero Valent Iron Oxide Nanoparticles and Chitosan for Removal of Arsenic in Contaminated Water
Bibliographic record
Abstract
Water contaminated with highly hazardous metals including arsenic (As) is one of the major challenges faced by mankind in the present day. To address this pressing issue, hybrid beads were synthesized with various concentrations of zero valent iron oxide nanoparticles, i.e., 20% (FeCh-20), 40% (FeCh-40) and 60% (FeCh-60) impregnated into a polymer of chitosan. These hybrid beads were employed as an adsorbent under the optimized conditions of pH and time to facilitate the efficient removal of hazardous arsenic by adsorption cum reduction processes. X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), Brunauer- Emmett-Teller BET, a porosity test and wettability analysis were performed to characterize these hybrid beads. The porosity and contact angle of the prepared hybrid beads decreased with an increase in nanoparticle concentration. The effects of various adsorption factors such as adsorbent composition, contact period, pH value and the initial adsorbate concentration were also evaluated to study the performance of these beads for arsenic treatment in contaminated water. FeCh-20, FeCh-40 and FeCh-60 have demonstrated 63%, 81% and 70% removal of arsenic at optimized conditions of pH 7.4 in 10 h, respectively. Higher adsorption of arsenic by FeCh-40 is attributed to its optimal porosity, hydrophilicity and the presence of appropriate nanoparticle contents. The Langmuir adsorption kinetics described the pseudo second order. Thus, the novel beads of FeCh-40 developed in this work are a potent candidate for the treatment of polluted water contaminated with highly toxic arsenic metals.
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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 | 0.000 |
| 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) | 0.000 | 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".