Effectiveness of the dispersion of iron nanoparticles within micropores and mesopores of activated carbon for Rhodamine B removal in wastewater by the heterogeneous Fenton process
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Iron-based nanoparticles were formed in the pores of a micro- and mesoporous activated carbon made from banana spike by the impregnation of iron sulfate at various ratios and further pyrolysis, in order to prepare three catalysts AC@Fe/1, AC@Fe/2, AC@Fe/3 having iron mass contents of 1.6%, 2.2% and 3.3%, respectively. The pore size distributions, transmission electron microscope observations and X-ray photoelectron spectroscopy analyses have revealed that iron-based nanoparticles of 1–50 nm diameter, containing O and P, are located mainly in the supermicropores and mesopores of the activated carbon. Catalysts have been used to remove Rhodamine B in an aqueous solution by the heterogeneous Fenton process. AC@Fe/3 catalyst has allowed achieving 93% of solution discoloration compared to 87.4% for AC@Fe/2 and 78.5% for AC@Fe/1 after 180 min in batch reaction. The catalytic efficiency of AC@Fe/3 is attributed to the highest dispersion of the iron-based nanoparticles in the activated carbon porosity. The effects of hydrogen peroxide and initial dye concentration, pH, catalyst amount and temperature on the Rhodamine B removal kinetics catalyzed by AC@Fe/3 were studied. This catalyst showed remarkable performances of the Rhodamine B mineralization and possibility of recycling.
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.
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 | 0.001 | 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 | 0.001 |
| 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 it