Crystal-plane-dependent metal–support interaction in Au/TiO<sub>2</sub>
Bibliographic record
Abstract
Metal-support interactions between Au and TiO2 are studied based on Au/TiO2 catalysts with different TiO2 crystal planes exposed. With ex situ XPS, TEM and in situ DRIFTS, we have investigated the crystal-plane-dependent metal-support interaction effects on the physiochemical properties of Au/TiO2 catalysts. Based on the structural characterization and spectroscopic results, we can observe chemical oscillations (including the electronic structures of Au nanoparticles and the interaction between Au/TiO2 catalysts and CO molecules) during alternate H2 and O2 pre-treatments. Their variation tendencies of oscillations are greatly dependent on the crystal planes of TiO2 and the pre-treatment temperature. Furthermore, their surface and electronic changes after H2 and O2 pre-treatments can be well correlated with their catalytic activities in CO oxidation. Electron-transfer processes across the Au-TiO2 interface are proved to be the origin accounting for their changes after H2 and O2 pre-treatments. The different electronic structures of different TiO2 crystal planes should have relationships with the crystal-plane-dependent metal-support interaction effects in Au/TiO2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".