Direct Liquid Reactor-Injector of Nanoparticles: A Safer-by-Design Aerosol Injection for Nanocomposite Thin-Film Deposition Adapted to Various Plasma-Assisted Processes
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Bibliographic record
Abstract
The requirements of nanocomposite thin films, having non-aggregated nanoparticles homogeneously dispersed in the matrix, have been realized using a new method of Direct Liquid Reactor-Injector (DLRI) of nanoparticles. In this approach, unlike conventional aerosol-assisted plasma deposition, the nanoparticles are synthesized before their injection as an aerosol into plasma. In our experiments, we have used two different plasma reactors, namely an asymmetric low-pressure RF plasma reactor and a parallel plate dielectric barrier discharge at atmospheric pressure. Our results have shown that DLRI can be easily coupled with various plasma processes as this approach allows the deposition of high-quality multifunctional nanocomposite thin films, with embedded nanoparticles of less than 10 nm in diameter. Hence, DLRI coupled with plasma processes meets the specifications for the deposition of multifunctional coatings.
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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 | 0.001 |
| 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