Surface Chemistry of Gold Nanoparticles Produced by Laser Ablation in Aqueous Media
Why this work is in the frame
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Bibliographic record
Abstract
The femtosecond laser ablation of a gold target in aqueous solutions has been used to produce colloidal Au nanoparticles with controlled surface chemistry. A detailed chemical analysis showed that the nanoparticles formed were partially oxidized by the oxygen present in solution. The hydroxylation of these Au−O compounds, followed by a proton loss to give surface Au−O -, resulted in the negative charging of the nanoparticles. The partial oxidation of the gold nanoparticle surface enhances its chemical reactivity and consequently has a strong impact on its growth. In particular, the oxidized surface reacted efficiently with Cl - and OH - to augment its net surface charge. This limited the coalescence of the particles, due to electrostatic repulsion, and led to a significant reduction of their size. Taking advantage of the repulsion effect, efficient size control was achieved using different salts (7 ± 5 nm for 10 mM KCl, 5.5 ± 4 nm for 10 mM NaCl, 8 ± 5 nm for NaOH, pH 9.4), a considerable improvement comparatively to particles prepared in deionized water, using identical ablation conditions, where particles of 1−250 nm were produced. The partially oxidized gold surface was also suitable for surface modification through both covalent and electrostatic interactions during particle formation. Using solutions of N -propylamine, we showed an efficient control of nanoparticle size (5−8 ± 4−7 nm) by the involvement of these interactions. The results obtained help to develop methodologies for the control of laser-ablation-based nanoparticle growth and the functionalization of nanoparticle surfaces by specific interactions.
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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