Reduced Ensemble Plasmon Line Widths and Enhanced Two-Photon Luminescence in Anodically Formed High Surface Area Au–TiO<sub>2</sub> 3D Nanocomposites
Bibliographic record
Abstract
Localized surface plasmon resonances (LSPR) in TiO 2 nanorod and nanotube arrays decorated by gold nanoparticles can be exploited to improve photocatalytic activity, enhance nonlinear optical coefficients, and increase light harvesting in solar cells. However, the LSPR typically has a low quality factor, and the resonance is often obscured by the Urbach tail of the TiO 2 band gap absorption. Attempts to increase the LSPR extinction intensity by increasing the density of gold nanoparticles on the surface of the TiO 2 nanostructures invariably produce peak broadening due to the effects of either agglomeration or polydispersity. We present a new class of hybrid nanostructures containing gold nanoparticles (NPs) partially embedded in nanoporous/nanotubular TiO 2 by performing the anodization of cosputtered Ti–Au thin films containing a relatively high ratio of Au:Ti. Our method of anodizing thin film stacks containing alternate layers of Ti and TiAu results in very distinctive LSPR peaks with quality factors as high as 6.9 and ensemble line widths as small as 0.33 eV even in the presence of an Urbach tail. Unusual features in the anodization of such films are observed and explained, including oscillatory current transients and the observation of coherent heterointerfaces between the Au NPs and anatase TiO 2 . We further show that such a plasmonic NP-embedded nanotube structure dramatically outperforms a plasmonic NP-decorated anodic nanotube structure in terms of the extinction coefficient, and achieves a strongly enhanced two-photon fluorescence due to the high density of gold nanoparticles in the composite film and the plasmonic local field enhancement.
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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".