Enhancing Galvanic Replacement in Plasmonic Hollow Nanoparticles: Understanding the Role of the Speciation of Metal Ion Precursors
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Bibliographic record
Abstract
Abstract Hollow nanostructures offer great potential for plasmonic applications due to their strong and highly tunable localized surface plasmon resonance. The relationship between the plasmonic properties and geometry of hollow nanoparticles, such as core‐shell size ratio, concentricity of the cavity and porosity of the wall, is well documented. Nanoscale galvanic replacement provides a simple, versatile and powerful route for the preparation of such hollow structures. Here we demonstrate how the efficiency of reductant‐assisted galvanic replacement processes can be enhanced by controlling the degree of hydration and hydrolysis of the metal ion precursor using pH and pL as key control parameters (by analogy to pH, the letter p in the expression pL is used to indicate the decimal cologarithm associated with the concentration of the ligand L). Adjusting precursor speciation prior to the sacrificial template's hollowing process offers a new strategy to tune the morphology and optical properties of plasmonic hollow nanostructures.
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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 | 0.000 | 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 it