The property-governed activity of silver-modified titania photocatalysts: The influence of titania matrix
Bibliographic record
Abstract
Commercial titania photocatalysts were modified with silver nanoparticles (NPs) by the photodeposition method in the presence/absence of methanol. The obtained photocatalysts were characterized by XRD, XPS, diffuse reflectance spectroscopy, STEM, and time-resolved microwave conductivity (TRMC) methods. The photocatalytic activity was tested under UV/vis irradiation for (i) methanol dehydrogenation (during silver deposition), (ii) oxygen evolution with in situ silver deposition, and (iii) oxidative decomposition of acetic acid, as well as under vis irradiation for 2-propanol oxidation. The action spectra of 2-propanol oxidation were also performed. It has been confirmed that modification of titania with silver causes significant improvement of photocatalytic activity under both UV and vis irradiation as silver works as an electron scavenger (TRMC data) and vis activator (possibly by an energy transfer mechanism). The obtained activities differ between titania samples significantly, suggesting that the type of crystalline phase, particle/crystallite sizes, and electron traps' density are crucial for both the properties of formed silver deposits and resultant photocatalytic activity. It might be concluded that, under UV irradiation, (i) high crystallinity and large specific surface area are recommended for rutile- and anatase-rich samples, respectively, during hydrogen evolution, (ii) mixed crystalline phases cause a high rate of oxygen evolution from water, and (iii) anatase phase with fine silver NPs results in efficient decomposition of acetic acid, whereas under vis irradiation the aggregated silver NPs (broad localized surface plasmon resonance peak) on the rutile phase are promising for oxidation reactions.
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".