Surface Modified Mesostructured Iron Oxyhydroxide: Synthesis, Ecotoxicity, and Application
Bibliographic record
Abstract
Mesoporous iron oxide, particularly amine-functionalized FeO(x) and FeO(x), was investigated for the removal of toxic heavy metal anions of arsenic and chromium from an aqueous solution. As a control experiment for these toxic compounds, adsorption tests were also performed on Fe3O4 as their counterpart bulk chemical. The mesostructures were confirmed by X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) and transmission electron microscopy (TEM). In addition, we prepared stock suspensions of meso-FeO(x), amine-functionalized meso-FeO(x) and Fe3O4 particles, and compared their acute toxicity against Daphnia magna. The 24 h-EC50 values of the amine-functionalized meso-FeO(x), meso-FeO(x) and Fe particle suspensions used in this study were 1682, 2549 and 95 mg/L, respectively. Organism toxicity caused by spills of adsorbents can be negated when the amine-functionalized meso-FeO(x), up to 1500 mg/L, is used as the adsorbent for heavy metal treatment. The adsorption of arsenic and chromium by the three adsorbents were examined, and different adsorption models were used to describe the equilibrium and kinetic data. The amine-functionalized meso-FeO(x) adsorbent was found to give the maximum adsorption capacities for arsenic and chromium (33.51 and 25.05 mg/g, respectively). This research gives promising results for the application of modified meso-FeO(x) as an adsorbent of toxic heavy metal anions from aqueous solutions.
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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 | 0.000 | 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 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".