Strategies to improve the photocatalytic activity of TiO<sub>2</sub>: 3D nanostructuring and heterostructuring with graphitic carbon nanomaterials
Bibliographic record
Abstract
TiO2-based photocatalysis has been considered to be one of the most promising avenues for environmental remediation including water purification. However, several technical issues such as the limited surface area of bulk TiO2, the large band gap of TiO2, and rapid charge recombination still limit the practical application of TiO2 photocatalysts. Therefore, here we focus on two structural design strategies: (i) monolithic three-dimensional (3D) nanostructuring, and (ii) heterostructuring with graphitic carbon nanomaterials. A monolithic 3D nanostructure enables maximal surface area in a given volume and efficient reuse of the photocatalyst without recollection. Heterostructuring with carbon nanomaterials helps achieve maximal utilization of the solar spectrum and charge separation and provides efficient TiO2 photocatalysts. In this review, recent progress on TiO2 photocatalysts toward the abovementioned strategies will be summarized. Further discussion and direction will provide insights into the rational design of highly efficient TiO2 photocatalysts, and help develop advanced photocatalyst models.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".