Reduced Graphene Oxide-Based Foam as an Endocrine Disruptor Adsorbent in Aqueous Solutions
Bibliographic record
Abstract
A stable and magnetic graphene oxide (GO) foam-polyethyleneimine-iron nanoparticle (GO-PEI-FeNPs) composite has been fabricated for removal of endocrine disruptors-bisphenol A, progesterone and norethisterone-from aqueous solution. The foam with porous and hierarchical structures was synthesized by reduction of graphene oxide layers coupled with co-precipitation of iron under a hydrothermal system using polyethyleneimine as a cross linker. The presence of magnetic iron nanoparticles facilitates the separation process after decontamination. The foam was fully characterized by surface and structural scanning electron microscopy, Fourier transform infrared spectroscopy, Raman spectroscopy and X-ray photoelectron spectroscopy. The foam exhibits a high adsorption capacity, and the maximum adsorption percentages are 68%, 49% and 80% for bisphenol A, progesterone and norethisterone, respectively. The adsorption process of bisphenol A is explained according to the Langmuir model, whereas the Freundlich model was used for progesterone and norethisterone adsorption.
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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".