Effect of Oxygen Content on the Photoelectrochemical Activity of Crystallographically Preferred Oriented Porous Ta<sub>3</sub>N<sub>5</sub> Nanotubes
Bibliographic record
Abstract
Crystallographically preferred oriented porous Ta 3 N 5 nanotubes (NTs) were synthesized by thermal nitridation of vertically oriented, thick-walled Ta 2 O 5 NTs, strongly adhered to the substrate. The adherence on the substrate and the wall thickness of the Ta 2 O 5 NTs were fine-tuned by anodization, thereby helping to preserve their tubular morphology for nitridation at higher temperatures. Samples were studied by scanning electron microscopy, high-resolution electron microscopy, X-ray diffraction, Rietveld refinements, ultraviolet–visible spectrophotometry, X-ray photoelectron spectroscopy, photoluminescence spectra, and electrochemical techniques. Oxygen content in the structure of porous Ta 3 N 5 NTs strongly influenced their photoelectrochemical activity. Structural analyses revealed that the nitridation temperature has crystallographically controlled the preferential orientation along the (110) direction, reduced the oxygen content in the crystalline structure and the tubular matrix, and increased the grain size. The preferred oriented porous Ta 3 N 5 NTs optimized by the nitridation temperature presented an enhanced photocurrent of 7.4 mA cm –2 at 1.23 V vs RHE under AM 1.5 (1 Sun) illumination. Hydrogen production was evaluated by gas chromatography, resulting in 32.8 μmol of H 2 in 1 h from the pristine porous Ta 3 N 5 NTs. Electrochemical impedance spectroscopy has shown an effect of nitridation temperature on the interfacial charge transport resistance at the semiconductor–liquid interface; however, the flat band of Ta 3 N 5 NTs remained unchanged.
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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".