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 TiO2/SiO2 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 N2 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 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".