Physicochemical Study of Photocatalytic Activity of TiO<sub><b>2</b></sub>Supported Palygorskite Clay Mineral
Bibliographic record
Abstract
This study deals with the influence of physicochemical parameters, namely, the photocatalyst loading, dye concentration, and pH of polluted solutions, on the degradation efficiency of Orange G (OG) solutions containing TiO 2 nanoparticles supported on palygorskite clay mineral (TiO 2 -Pal). The TiO 2 photocatalyst attached to natural palygorskite fibers was elaborated by colloidal sol-gel route. It exhibits the anatase structure that is the most photoactive crystallographic form. The highest performances of supported photocatalyst on OG degradation were found using an optimum amount of TiO 2 -Pal around 0.8 g·L −1 , which corresponds properly to ca . 0.4 g·L −1 of TiO 2 . This amount is interestingly lower than the 2.5 g·L −1 generally reported when using pure unsupported TiO 2 powder. The photodegradation rate increases by decreasing OG initial concentration, and it was found significantly higher when the OG solution is either acidic (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mtext>pH</mml:mtext><mml:mo><</mml:mo><mml:mn>4</mml:mn></mml:math>) or basic (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mtext>pH</mml:mtext><mml:mo>≈</mml:mo><mml:mn>11</mml:mn></mml:math>). For OG concentrations in the range<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mn>5</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>-</mml:mo><mml:mn>6</mml:mn></mml:mrow></mml:msup><mml:mtext>–</mml:mtext><mml:mi> </mml:mi><mml:mn>5</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>-</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:msup></mml:math> M, the kinetic law of the OG degradation in presence of TiO 2 -Pal is similar to that reported for unsupported TiO 2 nanopowder. It follows a Langmuir-Hinshelwood model with a first-order reaction and an apparent rate constant of about<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mn>2.9</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mrow><mml:mn>10</mml:mn></mml:mrow><mml:mrow><mml:mo>-</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math> min −1 .
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".