CO<sub>2</sub> Photoreduction Activity Enhancement and Unexpected Observation of Carbon Monoxide Adsorbates on the Surface of TiO<sub>2</sub> Nanotube Arrays Synthesized in Formamide Electrolytes
Bibliographic record
Abstract
TiO 2 nanotube arrays grown through electrochemical anodization in a formamide-based electrolyte (TNTA-FA) exhibited a whole host of unusual properties compared to nanotubes grown in the conventional ethylene glycol-based electrolyte (TNTA-EG). TNTA-FA exhibited shorter phonon lifetimes, lower lattice strain, more visible light absorption, lower work function, and a highly unusual adsorbate structure consisting of physisorbed and chemisorbed CO along with linearly adsorbed CO 2 and various monodentate and bidentate carbonate species. The observation of adsorbed CO in the dark is highly unusual and indicates spontaneous deoxygenation of CO 2 on the surface of TNTA-FA. The significance of this finding is that the formation of CO 2 •– is no longer the rate-limiting bottleneck for the reduction of CO 2 on TNTA-FA surfaces as it is for all TiO 2 surfaces. TNTA-FA samples are strongly colored (inclusive of a fluorescent green color) and consist of rounded, vertically oriented hollow cylinders as opposed to the honeycomb-like morphology of TNTA-EG arranged in an approximate triangular lattice. The photocatalytic activity was tested through the CO 2 photoreduction and dye degradation tests. Formamide-based nanotubes outperformed the EG-based nanotubes by almost 1.7 and 2 times, respectively, in CO 2 reduction and dye degradation tests done on methylene blue, brilliant green, and rhodamine B dyes. These results are attributed to stronger surface band bending in TNTA-FA which facilitates more efficient separation of photogenerated electron–hole pairs.
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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) | 0.000 | 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".