Studying the Generation of Hot Electrons in Plasmonic Nanoparticle Monolayers
Bibliographic record
Abstract
Hot electrons are generated from the decay of LSPR modes.Surface-enhanced Raman spectroscopy is used to monitor hot electron generation using a dehalogenation reaction.In this thesis, Ag, Au, and AuAg nanoparticle substrates were produced and coated with halogenated thiophenols.The dipole and coupled LSPR modes associated with the nanoparticle substrate both generate hot electrons under illumination.The hot electron yield was determined for each LSPR modes.It was found that the dipole LSPR mode produced a larger yield of hot electrons than the coupled LSPR mode.The enhanced hot electron yield for the dipole mode was reported for both Ag-slides and AuAg-slides; additionally, the same result was obtained for both halogenated thiophenols.This work shows that the dipole LSPR mode is more suitable for the generation of hot electron than the coupled mode.Additional work is required to make the coupled LSPR mode an efficient hot electron generator.
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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".