Chemical stability and degradation mechanisms of triangular Ag, Ag@Au, and Au nanoprisms
Bibliographic record
Abstract
Anisotropic metal nanoparticles have found use in a variety of plasmonic applications because of the large near-field enhancements associated with them; however, the very features that give rise to these enhancements (e.g., sharply curved edges and tips) often have high surface energies and are easily degraded. This paper describes the stability and degradation mechanisms of triangular silver, gold-coated silver, and gold nanoprisms upon exposure to a wide variety of adverse conditions, including halide ions, thiols, amines and elevated temperatures. The silver nanoprisms were immediately and irreversibly degraded under all of the conditions studied. In contrast, the core-shell Ag@Au nanoprisms were less susceptible to etching by chlorides and bromides, but were rapidly degraded by iodides, amines and thiols by a different degradation pathway. Only the pure gold nanoprisms were stable to all of the conditions tested. These results have important implications for the suitability of triangular nanoprisms in many applications; this is particularly true in biological or environmental fields, where the nanoparticles would inevitably be exposed to a wide variety of chemical stimuli.
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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 | 0.001 |
| 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".