Silver Nanoparticles Formation by Nanosecond Pulsed Laser Irradiation in an Aqueous Solution of Silver Nitrate; Effect of Sodium bis (2-ethyl hexyl) Sulfosuccinate
Bibliographic record
Abstract
A photochemical reduction of a silver salt precursor using near-ultra-violet (UV) pulsed laser (355 nm) irradiation into aqueous surfactant sodium-bis (2–ethylhexyl) sulfosuccinate (AOT) solution has succeeded in synthesizing homogenous speculative silver nanoparticles (Ag NPs). Without using any additive, the irradiation from ns laser pulses to aqueous silver nitrate solution was observed to create nanocubes (NCs). The photoproduct was transformed into a nanosphere when irradiated with a particular AOT concentration. The photoproduct concentration of NCs to NSs was approximately ten times lower than the critical concentration of micellar (CMC) in AOT, which means that the growth of NSs was aided in a single layer of AOT adsorbed on silver surfaces. A UV / Visible Spectrophotometer and Transmission/Scanning electron microscopy (TEM/SEM) were used to characterize the photochemically synthesized sample thoroughly. The mean size of AgNSs, analyzed by TEM, was 8 nm. These parameters have shown the growth of AgNSs and discussed in the paper. These nanoparticles are potential candidates for catalyst, semiconductor, photovoltaic equipment, medical diagnostics applications than bulk materials.
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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 | 0.000 |
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".