Tuning of Morphology and Stability of Gold Nanostars Through pH Adjustment
Bibliographic record
Abstract
In this study, the morphology and stability of gold nanostars (AuNSs) were investigated under different pH environments. The surface morphologies and plasmonic properties were observed for nanostars (NSs) deposited on glass substrates, using SEM and ultraviolet and visible (UV-Vis) spectroscopy. It is found that gold nanostars can be readily stabilized just by adjusting the initial pH condition of the growth solution. The particle size distribution of gold nanostars under different pH environments has been investigated using UV-Vis spectroscopy and found to be highly dependent on pH. At the optimal pH of 11, the gold nanostars are highly monodisperse, they have longer branches and the Au Localized Surface Plasmon Resonance band (LSPR) at 720 nm. For other pH conditions, particles are non-uniform and polydisperse, showing a red-shift of the plasmon peak due to aggregation and a large particle size distribution. Time-dependent UV-Vis spectra studies hypothesize the pH dependent stabilization mechanism, where the formation and stabilization of AuNS were affected greatly by the aggregation induced by pH of the growth solution. The information obtained in this study can be used to design stable gold nanostars with longer shelf life for biosensing applications.
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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 | 0.001 |
| 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 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".