Spectroscopic Insights into Controlling Sidewall Faceting of TiO <sub>2</sub> Nanowires via Au–Ag Bimetallic Seeds
Bibliographic record
Abstract
Precisely controlling the morphology and crystallographic features of single-crystalline, defect-free nanowires is key to advancing their applications. This study demonstrates that the local compositional heterogeneity within Au–Ag bimetallic seeds─specifically the presence of Ag-rich domains at a particular corner of the seed–nanowire interface─drives a transition from ⟨110⟩-oriented bead-like TiO 2 nanowires to ⟨111⟩-oriented prismatic nanowires during vapor-phase growth. The strong affinity between Ag and oxygen-containing growth species, as identified through X-ray absorption spectroscopy and electron energy loss spectroscopy, facilitates site-specific nucleation and lateral growth across the hexagonal seed–nanowire interface for prismatic nanowires. These findings underscore the critical role of localized seed composition at the seed–nanowire interface in governing nucleation behavior and enabling controlled nanowire morphology through seed engineering.
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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".