Synthesis and characterization of visible light driven N—Fe‐codoped TiO<sub>2</sub>/SiO<sub>2</sub> for simultaneous photoremoval of Cr (VI) and azo dyes in a novel fixed bed continuous flow photoreactor
Bibliographic record
Abstract
Abstract N─Fe‐codoped TiO 2 /SiO 2 nanocomposites were prepared and stabilized onto glass beads by coupling two methods of dip coating and heat attachment. The prepared nanocomposites were characterized by DRS‐UV/vis, FTIR, XRD, FESEM, EDX, TEM, XPS, and N 2 adsorption/desorption analyses. The operational parameters of pH, flow rate, and the photoreactor's angle against sunlight were optimized to achieve the highest degradation efficiency. Then, the photocatalytic efficacy of the prepared substrates was examined in a novel fabricated photoreactor on a complex pollutant mixture consisting of Cr (VI), BR‐29, BB‐41, and BY‐51, under two irradiation sources of visible light and sunlight. Moreover, to virtualize the process under natural irradiation conditions, the effectiveness of the performance was evaluated in various outdoor climate circumstances. Consequently, the results demonstrated the enhanced photocatalytic activity of the prepared nanocomposites under visible and solar irradiations. The removal percentages were also considerable under a partly cloudy sky and were 91.73%, 85.64%, 87.23%, and 58.59% for Cr (VI), BR‐29, BB‐41, and BY‐51, respectively. The results showed the promising activity of the innovative photoreactor and the as‐prepared nanocomposites for photocatalytic remediation of the water pollutants under natural climate conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".