Synthesis of surfactant-free electrostatically stabilized gold nanoparticles by plasma-induced liquid chemistry
Bibliographic record
Abstract
Plasma-induced non-equilibrium liquid chemistry is used to synthesize gold nanoparticles (AuNPs) without using any reducing or capping agents. The morphology and optical properties of the synthesized AuNPs are characterized by transmission electron microscopy (TEM) and ultraviolet-visible spectroscopy. Plasma processing parameters affect the particle shape and size and the rate of the AuNP synthesis process. Particles of different shapes (e.g. spherical, triangular, hexagonal, pentagonal, etc) are synthesized in aqueous solutions. In particular, the size of the AuNPs can be tuned from 5 nm to several hundred nanometres by varying the initial gold precursor (HAuCl4) concentration from 2.5 μM to 1 mM. In order to reveal details of the basic plasma-liquid interactions that lead to AuNP synthesis, we have measured the solution pH, conductivity and hydrogen peroxide (H2O2) concentration of the liquid after plasma processing, and conclude that H2O2 plays the role of the reducing agent which converts Au(+3) ions to Au(0) atoms, leading to nucleation growth of the AuNPs.
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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) | 0.001 | 0.001 |
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".