Role of the TiO<sub>2</sub> Crystalline Phase in Pt-TiO<sub>2</sub> for Thermocatalytic Mineralization of Gaseous Acetaldehyde
Bibliographic record
Abstract
Pt-TiO 2 is an efficient low-temperature thermocatalyst for volatile organic compound (VOC) removal, driven by active oxygen species formation through metal–support interactions. While the role of Pt is well established, the influence of TiO 2 polymorphs on active oxygen generation is less understood. This study explores the thermocatalytic removal of acetaldehyde (CH 3 CHO) over Pt supported on three TiO 2 polymorphs: anatase, rutile, and brookite. CH 3 CHO mineralization at 160 °C follows the trend: Pt-anatase (99.5%) > Pt-rutile (79.3%) > Pt-brookite (56.7%). These differences correlate with the oxygen adsorption and active oxygen generation capabilities, as evidenced by electrochemical analyses and O 2 -temperature-programmed desorption. Density functional theory calculations further indicate that Pt supported on anatase has the highest negative charge density, which significantly enhances the formation of active oxygen species. In situ FTIR spectroscopy provides additional evidence by revealing distinct CH 3 CHO oxidation pathways: *HCOOH on Pt-anatase and Pt-brookite, and *CH 3 COOH on Pt-rutile. Despite sharing a similar pathway, Pt-anatase displayed faster kinetics due to a higher abundance of surface-active oxygen species. This study highlights the pivotal role of TiO 2 polymorphs in shaping metal–support interactions and provides critical insights for designing efficient Pt-based catalysts for thermocatalytic VOC abatement.
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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) | 0.001 | 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".