Preferentially oriented TiO <sub>2</sub> nanotube arrays on non-native substrates and their improved performance as electron transporting layer in halide perovskite solar cells
Bibliographic record
Abstract
Abstract Anodically formed TiO 2 nanotube arrays (TNTAs) constitute an optoelectronic platform that is being studied for use as a photoanode in photoelectrocatalytic cells, as an electron transport layer (ETL) in solar cells and photodetectors, and as an active layer for chemiresistive and microwave sensors. For optimal transport of charge carriers in these one-dimensional polycrystalline ordered structures, it is desirable to introduce a preferential texture with the grains constituting the nanotube walls aligned along the transport direction. Through x-ray diffraction analysis, we demonstrate that choosing the right water content in the anodization electrolyte and the use of a post-anodization zinc ion treatment can introduce a preferential texture in sub-micron length transparent TNTAs formed on non-native substrates. The incorporation of 1.5 atom% of Zn in TiO 2 nanotubes prior to annealing, was found to consistently result in the strongest preferential orientation along the [001] direction. [001] oriented TNTAs exhibited a responsivity of 523 A W −1 at a bias of 2 V for 365 nm photons, which is among the highest reported performance values for ultraviolet photodetection using titania nanotubes. Furthermore, the textured nanotubes without a Zn 2+ treatment showed a significantly enhanced performance in halide perovskite solar cells that used TNTAs as the ETL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".