Recent progress on Ti-based piezo-photocatalysts for wastewater treatment
Bibliographic record
Abstract
Piezo-photocatalysis has emerged as a promising hybrid advanced oxidation process to eliminate resistant organic pollutants in wastewater via harnessing light irradiation and mechanical vibration. This process offers a synergistic enhancement of photocatalytic efficiency by coupling piezo-electricity with photocatalytic activity, addressing limitations of conventional photocatalysis, including rapid electron-hole pairs recombination and deactivation in the absence of illumination. We concisely review recent advancements in Ti-based piezo-electric semiconductors for wastewater treatment, focusing on research from 2020 to 2025. The studies included in this review are based on materials categorized into two main groups: integrated Ti-based piezo-photocatalysts and hybrid piezo-electric materials-incorporated TiO 2 photocatalysts. We critically discuss the impact of piezo-potential and corresponding internal electric fields on photoinduced charge separation and reactive oxygen species generation. Methodologies for assessing the piezo-electric and photocatalytic properties are explored. This review highlights piezo-photocatalysis’s potential applications and challenges, offering insights into future developments in advanced oxidation processes for wastewater treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".