Insights into the growth of nanoparticles in liquid polyol by thermal annealing
Bibliographic record
Abstract
We report on the growth of metal- and metal-oxide based nanoparticles (NPs) in heated polyol solutions. For this purpose, NPs are produced by the sputtering of a silver, gold, or a copper target to produce either silver, gold, or copper oxide NPs in pentaerythritol ethoxylate (PEEL) which has been annealed up to 200 °C. The objective of the annealing step is the fine modulation of their size. Thus, the evolution of the NP size and shape after thermal annealing is explained according to collision/coalescence kinetics and the affinity between the metal-/metal-oxide and PEEL molecule. Moreover, highlights of few phenomena arising from the annealing step are described such as (i) the reduction of copper oxide into copper by the polyol process and (ii) the effective formation of carbon dots after annealing at 200 °C.
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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 | 0.000 | 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 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".