Designing green self-healing anticorrosion conductive smart coating for metal protection
Bibliographic record
Abstract
Abstract The development of an electrically-conductive anticorrosion coating with self-healing capability for metallic surface protection constitutes a priority concern for many key industrial applications. While current technologies largely rely on hazardous chromate-based corrosion inhibitors, this work proposes a simple polymer-based layer-by-layer (LBL) architecture, implemented using easy and fast fabrication techniques. Moreover, this smart coating architecture relies on three environmentally friendly polymers namely polyethylenimine (PEI), polystyrenesulfonate (PSS) and 8-hydroxyquinoline (8HQ) respectively serving as poly-cation, poly-anion and as corrosion inhibitor. Here, this protective coating is deposited and tested on the widely-used Aluminium 2024 alloy to achieve long term protection against corrosion. When structural damages to the coating occur, the inhibitor agents are released to passivate the surface. Raman micro-spectroscopy measurements confirm this effective self-healing capability. This chromate-free coating shows great promises for multiple aerospace, construction and automotive applications.
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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".