Fe doped TiO<sub>2</sub>–graphene nanostructures: synthesis, DFT modeling and photocatalysis
Bibliographic record
Abstract
In this work, Fe-doped TiO(2) nanoparticles ranging from a 0.2 to 1 weight % were grown from the surface of graphene sheet templates containing -COOH functionalities using sol-gel chemistry in a green solvent, a mixture of water/ethanol. The assemblies were characterized by a variety of analytical techniques, with the coordination mechanism examined theoretically using the density functional theory (DFT). Scanning electron microscopy and transmission electron microscopy images showed excellent decoration of the Fe-doped TiO(2) nanoparticles on the surface of the graphene sheets >5 nm in diameter. The surface area and optical properties of the Fe-doped photocatalysts were measured by BET, UV and PL spectrometry and compared to non-graphene and pure TiO(2) analogs, showing a plateau at 0.6% Fe. Interactions between graphene and Fe-doped anatase TiO(2) were also studied theoretically using the Vienna ab initio Simulation Package based on DFT. Our first-principles theoretical investigations validated the experimental findings, showing the strength in the physical and chemical adsorption between the graphene and Fe-doped TiO(2). The resulting assemblies were tested for photodegradation under visible light using 17β-estradiol (E2) as a model compound, with all investigated catalysts showing significant enhancements in photocatalytic activity in the degradation of E2.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".