Modulating Ti<i>t</i><sub>2g</sub>Orbital Occupancy in a Cu/TiO<sub>2</sub>Composite for Selective Photocatalytic CO<sub>2</sub>Reduction to CO
Bibliographic record
Abstract
Abstract The electronic structure of composites plays a critical role in photocatalytic conversion, whereas it is challenging to modulate the orbital for an efficient catalyst. Herein, we regulated the t 2g orbital occupancy state of Ti to realize efficient CO 2 conversion by adjusting the amount of photo‐deposited Cu in the Cu/TiO 2 composite. For the optimal sample, considerable electrons transfer from the Cu d orbital to the Ti t 2g orbital, as proven by X‐ray absorption spectroscopy. The Raman spectra results also corroborate the electron enrichment on the Ti t 2g orbital. Further theoretical calculations suggested that the orbital energy of the Ti 3d orbital in TiO 2 is declined, contributing to accepting Cu 3d electrons. As a result, the Cu/TiO 2 composite exhibited an extremely high selectivity of 95.9 % for CO, and the productivity was 15.27 μmol g −1 h −1 , which is almost 6 times that of the original TiO 2 . Our work provides a strategy for designing efficient photocatalysis as a function of orbital regulation.
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".