Enhancing the photoelectrochemical response of TiO2 nanotubes through their nanodecoration by pulsed-laser-deposited Ag nanoparticles
Bibliographic record
Abstract
We report on the pulsed laser deposition (PLD) based nanodecoration of titanium dioxide (TiO2) nanotube arrays (NTAs) by Ag nanoparticles (NPs). We focus here on the investigation of the effect of the number of laser ablation pulses (NLP) of the silver target on both the average size of the Ag-NPs and the photoelectrochemical conversion efficiency of the Ag-NP decorated TiO2-NT based photoanodes. By varying the NLP, we were able to not only control the size of the PLD-deposited Ag nanoparticles from 20 to ∼50 nm, but also to increase concomitantly the surface coverage of the TiO2 NTAs by Ag-NPs. The red-shifting of the surface plasmon resonance peak of the PLD-deposited Ag-NPs deposited onto quartz substrates confirmed the increase of their size as the NLP is increased from 500 to 10 000. By investigating the photo-electrochemical properties of Ag-NP decorated TiO2-NTAs, by means of linear sweep cyclic voltammetry under UV-Vis illumination, we found that the generated photocurrent is sensitive to the size of the Ag-NPs and reaches a maximum value at NLP =500 (i.e.,; Ag-NP size of ∼20 nm). For NLP = 500, the photoconversion efficiency of the Ag-NP decorated TiO2-NTAs is shown to reach a maximum of 4.5% (at 0.5 V vs Ag/AgCl). The photocurrent enhancement of Ag-NP decorated TiO2-NTAs is believed to result from the additional light harvesting enabled by the ability of Ag-NPs to absorb visible irradiation caused by various localized surface plasmon resonances, which in turn depend on the size and interdistance of the Ag nanoparticles.
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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 | 0.001 | 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 | 0.001 | 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".