In-Situ One-Step Direct Loading of Agents in Poly(acrylic acid) Coating Deposited by Aerosol-Assisted Open-Air Plasma
Bibliographic record
Abstract
In biomaterials and biotechnology, coatings loaded with bioactive agents are used to trigger biological responses by acting as drug release platforms and modulating surface properties. In this work, direct deposition of poly(acrylic acid) coatings containing various agents, such as dyes, fluorescent molecules, was achieved by aerosol-assisted open-air plasma. Using an original precursors injection strategy, an acrylic acid aerosol was loaded with an aqueous aerosol and deposited on silicon wafers. Results clearly showed that agents dissolved in the aqueous aerosol were successfully entrapped in the final coating. The effect of aerosols concentration, flow rate, and treatment time, on the coating morphology and the amount of entrapped agents, was also investigated. It was demonstrated that this process has the potential to entrap a tunable amount of any sensible water-soluble agent without altering its activity. To the best of our knowledge, this is the first time that the loading of an aqueous aerosol in coatings deposited by plasma from a liquid aerosol precursor is reported. This innovative approach complements plasma deposition of coatings loaded with bioactive agents from aqueous aerosols with the use of non-volatile liquid precursors.
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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".