A color-coordinated approach to the flow synthesis of silver nanoparticles with custom morphologies
Bibliographic record
Abstract
In an effort to meet the high demand for silver nanostructures in both research and consumer applications, we devise a simple and readily scaleable photochemical method through which silver nanostructures of varying morphologies, sizes, and optical properties can be synthesized using batch and flow photochemical strategies. For the latter we build upon the application of a wrapped-lamp photochemical flow system recently developed by our group to enable sequential irradiation with several wavelengths of LEDs in series in an approach that we describe as "plasmon pushing". We find that this strategy can accelerate the conversion of silver nanoparticle seeds to decahedral and triangular nanostructures, and that with it we have control over the tuning of the size and optical properties of triangular nanostructures in the red and near-IR regions. Moreover, through sequential flow irradiation, we gain a better understanding of the formation pathways and relative stability of decahedral and triangular silver nanostructures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".