Upscaling Anodic Synthesis of TiO<sub>2</sub> Nanotubes Film as Potential Material for Photoelectrocatalytic Applications: Influence of Electrolyte Overheating and Aging on Nanotube Morphology and Stability
Bibliographic record
Abstract
Background: Among Advanced oxidation processes, heterogeneous photocatalysis have a great interest, because it uses only light has a source of energy. One of the main limiting processes in photocatalysis is the high probability of electron-hole pair’s recombination in the volume or at the surface of the photocatalyst particles. TiO2 nanotubes grown by anodic synthesis are widely studied because of the large number of potential practical applications especially in photocatalytic or photoelectrochemical applications. However, the preparation of these electrodes at large scale is still challenging due to some technological obstacles such as the electrochemical cell design or the precise control of nanotubes morphology, especially regarding electrolyte ageing and overheating during the synthesis. Objective: This study examines the electrochemical synthesis of TiO2 nanotubes supported on large titanium electrodes. Methods and Results: By understanding heat dissipation phenomenon during the synthesis, an optimized electrochemical cell was designed to prepare 6x4 cm 2 anodes. Then we aimed to control precisely the length of the nanotubes independently of electrolyte ageing. Indeed, It was previously observed that the electrolyte composition evolves (ageing) during the nanotubes synthesis and hence leads to nonreproducible nanotubes morphologies under time-controlled potentiostatic anodization conditions. Conclusion and Perspectives: To overcome this issue, we developed a Coulometric approach that allows to synthesize, reusing the same electrolyte, several electrodes with a great precision and reproducibility on the length of the nanotubes (2,7 μm ± 160 nm) despite electrolyte ageing. Subsequently, these electrodes can be integrated in a photocatalytic or photoelectrocatalytic process in a real wastewater treatment sector would be very relevant.
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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".