Single‐Atom Photocatalysts on TiO <sub>2</sub> : Insights from X‐Ray Absorption Spectroscopy
Bibliographic record
Abstract
Abstract Surface modification of TiO 2 with single‐atom catalysts (SACs) is an effective strategy for enhancing photocatalytic efficiency. However, thorough characterization of SACs at the atomic scale remains challenging. X‐ray absorption spectroscopy (XAS) offers unique advantages for the in‐depth analysis of TiO 2 ‐supported SACs. By employing XAS, the local atomic structure, oxidation state, and electronic properties of the SACs, as well as the underlying photocatalytic mechanism, can be revealed. Herein, we present a short review on the application of XAS in studying TiO 2 ‐supported SACs. We first elucidate the key role of XAS in simultaneously probing the structure and electronic properties of monometallic SACs across different periods. Next, we discuss XAS studies of bimetallic SACs from the perspective of each constituent element and highlight the element‐specific capabilities of XAS for analyzing multi‐element SACs. Finally, we demonstrate how in situ XAS can effectively monitor structural and electronic property changes in SACs under real photocatalytic reaction conditions. Overall, this review highlights the unique advantages of XAS in achieving a more comprehensive understanding of the structure−property relationships in SACs, ultimately aiding the rational design of future photocatalysts. Additionally, we provide practical suggestions for utilizing XAS more efficiently in the analysis of various SAC systems.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".