Modification of Immobilized Titanium Dioxide Nanostructures by Argon Plasma for Photocatalytic Removal of Organic Dyes
Bibliographic record
Abstract
The aim of this study was to modify surface properties of immobilized rutile TiO₂ using Argon cold plasma treatment and to evaluate the performance of the catalyst in photocatalytic elimination of synthetic dyes in UV/TiO₂/H₂O₂ process. The surface-modified TiO₂ was characterized by XRD, EDX, SEM, UV-DRS and XPS analyses. Response surface methodology was adopted to achieve high catalyst efficiency by evaluating the effect of two main independent cold plasma treatment parameters (exposure time and pressure) on surface modification of the catalyst. The increase of the plasma operation pressure led to higher decolorization percentage, while the increase of plasma exposure time decreased the decolorization efficiency. RSM methodology predicted optimum plasma treatment conditions to be 0.78 Torr and 21 min of exposure time, which resulted in decolorization of 10 mg/L solution of the malachite green solution by 94.94% in 30 min. The plasma treatment decreased the oxygen to titanium ratio and caused oxygen vacancy on the surface of the catalyst, resulting in the superior performance of the plasma-treated catalyst. Pseudo first-order kinetic rate constant for the plasma-treated catalyst was 4.28 and 2.03 times higher than the rate constant for the non-treated photocatalyst in decolorization of aqueous solutions of malachite green and crystal violet, respectively.
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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".