Advanced Fabrication of Chemically Bonded Graphene/TiO2 Continuous Fibers with Enhanced Broadband Photocatalytic Properties and Involved Mechanisms Exploration
Bibliographic record
Abstract
Abstract In this article, a novel route for the synthesis of graphene/TiO 2 continuous fibers (GTF) using force-spinning combined with water vapor annealing method is reported for the first time. The morphology, structure and optical properties of the composite were fully characterized. With a single step of heat treatment process using steam at ambient conditions, we were able to initiate a series of chemical reactions, such as reduction of graphene oxide (GO), crystallization of TiO 2 , formation of C-Ti bond, and introduction of oxygen vacancies into TiO 2 . The incorporation of graphene in TiO 2 fibers facilitated bandgap narrowing and improved photo-induced charge separation in the photocatalyst. As a result of synergistic effects, TiO 2 fibers-2 wt% graphene (2%GTF) showed the highest photocatalytic activities in the degradation of X-3B under UV irradiation, superior to the benchmark photocatalyst P25. Under visible light irradiation, the same catalyst was about 4 times more efficient compared to pure TiO 2 fibers (PTF). A detailed study of involved active species (in particular, ·"Equation missing", h + and ·OH) unraveled the mechanism regarding photocatalysis.
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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 | 0.000 | 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".