Synthesis and Characterization of an α-Fe2O3-Decorated g-C3N4 Heterostructure for the Photocatalytic Removal of MO
Bibliographic record
Abstract
This study describes the preparation of graphitic carbon nitride (g-C3N4), hematite (α-Fe2O3), and their g-C3N4/α-Fe2O3 heterostructure for the photocatalytic removal of methyl orange (MO) under visible light illumination. The facile hydrothermal approach was utilized for the preparation of the nanomaterials. Powder X-ray diffraction (XRD), Scanning electron microscopy (SEM), Energy dispersive X-ray (EDX), and Brunauer–Emmett–Teller (BET) were carried out to study the physiochemical and optoelectronic properties of all the synthesized photocatalysts. Based on the X-ray photoelectron spectroscopy (XPS) and UV-visible diffuse reflectance (DRS) results, an energy level diagram vs. SHE was established. The acquired results indicated that the nanocomposite exhibited a type-II heterojunction and degraded the MO dye by 97%. The degradation ability of the nanocomposite was higher than that of pristine g-C3N4 (41%) and α-Fe2O3 (30%) photocatalysts under 300 min of light irradiation. The formation of a type-II heterostructure with desirable band alignment and band edge positions for efficient interfacial charge carrier separation along with a larger specific surface area was collectively responsible for the higher photocatalytic efficiency of the g-C3N4/α-Fe2O3 nanocomposite. The mechanism of the nanocomposite was also studied through results obtained from UV-vis and XPS analyses. A reactive species trapping experiment confirmed the involvement of the superoxide radical anion (O2•−) as the key reactive oxygen species for MO removal. The degradation kinetics were also monitored, and the reaction was observed to be pseudo-first order. Moreover, the sustainability of the photocatalyst was also investigated.
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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".