Facile Synthesis and Photothermal Stability of Silica‐Coated Gold Nanoworms
Bibliographic record
Abstract
Abstract Silica‐coated Au nanoparticles (NPs) have attracted significant attention due to their unique plasmon properties and biocompatibility. This is especially significant for NPs with their plasmon peaks in the near‐infrared (NIR) and within the therapeutic window. In this study, we have synthesized worm‐shaped Au NPs, called nanoworms (NWs) with an intense surface plasmon absorbance peak in the NIR, which were subsequently coated with silica. These NPs were then exposed to a nanosecond pulsed laser with varying fluences at a wavelength of 1064 nm and their UV–visible (vis) spectra were recorded to analyze the effects. Upon laser exposure, the longitudinal plasmon peaks exhibited a blue shift, which was more pronounced in the unmodified NWs. The silica‐coated NWs retained their optical properties even at higher laser fluences. However, for both bare and silica‐coated NWs, the required fluences to induce the shape modification were significantly higher than those previously reported for Au nanorods. These experiments highlight that the silica‐coated NWs are highly promising for biomedical applications, e.g., for various therapeutic and diagnostic uses, where maintaining performance under higher laser fluences is crucial.
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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".