TiO<sub>2</sub>membranes for concurrent photocatalytic organic degradation and corrosion protection
Bibliographic record
Abstract
Organic contaminants and corrosion in water treatment effluents are a current global problem and the development of effective methods to facilitate the removal of organic contaminants and corrosion control strategies are required to mitigate this problem. TiO2 nanomaterials that are exposed to UV light can generate electron-hole pairs, which undergo redox reactions to produce hydroxyl radicals from adsorbed molecular oxygen. They hydroxyl radicals are able to oxidize organic contaminants in water. This same process can be used in conjunction to protect metals from corrosion via cathodic polarization. In this work, TiO2 nanomaterials were synthesized and electrophoretically deposited on conductive substrates to serve as films or membranes. An illuminated TiO2 film on a conductive surface served as the photoanode and assisted in the cathodic protection of stainless steel (SS304) and the degradation of organic pollutants, in this case glucose. This proof-of-concept relied on photoelectrochemical experiments conducted using a potentiostat and a xenon lamp illumination source. The open-circuit potential changes that determine whether a metal is protected from corrosion under illumination was observed; and the electrical characteristics of the TiO2 film or membrane under dark and arc lamp illumination conditions were also analyzed. Furthermore, the effect of organic contaminants on the photocathodic protection mechanism and the oxidation of glucose during this process were explored.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".