Surfactant assisted dip-coating method for deposition of polyethylmethacrylate-diamond coatings
Bibliographic record
Abstract
This investigation is motivated by increasing interest in polymer-diamond coatings for biomedical applications in implants and sensors. A conceptually new strategy is based on the feasibility of solubilisation of polyethyl methacrylate (PEMA) in isopropanol using 18β-glycyrrhetinic acid (GRA) and rhamnolipids (RLP) as solubilising agents. This approach offers benefits for biomedical applications by avoiding the use of traditional toxic solvents for PEMA dissolution. The ability to obtain concentrated solutions of high molecular mass polymer is a crucial factor for the development of a dip coating method. Potentiodynamic and impedance spectroscopy studies indicate that PEMA films provide corrosion protection of stainless steel in 3% NaCl solutions. The use of GRA facilitates the fabrication of films with improved protective properties. PEMA films are obtained as monolayers or multilayers of controlled film mass. Another important finding is a good dispersion of chemically inert microdiamond and nanodiamond particles using GRA and RLP. For the first time composite PEMA-diamond films are obtained using GRA and RLP as solubilising agents for PEMA and dispersing agents for diamonds in isopropanol solvent. The detailed analysis of film microstructures provides an insight into the influence of chemical structure of GRA and RLP on their interactions with PEMA and diamonds. Moreover, microstructure analysis indicates that such interactions are important for preventing defects in the composite films. The benefits of steroid-like dispersants are discussed. Composite films are obtained as monolayers with different diamond content or PEMA-diamond multilayers of different composition and film mass. The method represents a versatile strategy for the fabrication of alternating PEMA/PEMA-diamond multilayers. The benefits of the obtained microstructures for biomedical applications are discussed. The approach developed in this investigation opens an avenue for the fabrication of other polymer coatings containing various functional 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".