Linseed oil derived terpolymer/silica nanocomposite materials for anticorrosive coatings
Bibliographic record
Abstract
Abstract Formulation of sustainable resource‐based organic–inorganic hybrid protective coatings have been achieved using Linseed oil‐based silica hybrid with terpolymer (TP) as basic skeletal matrix. The fabrication of TP system was performed by using systematic one pot multi‐facile steps (diol fatty amide–linseed oil‐based polyester amide TP) synthesis route. The conversion of ester amide functional ends of TP to urethane was initiated to enhance adhesiveness, impermeability, and corrosion resistivity of the processed hybrid material. FT‐IR and NMR ( 1 H, 13 C, and 29 Si) studies help in verifying the chemical structure and progress of the reaction. The formulation of smooth corrosion resistive coating was further analyzed by transmission electron microscopy, scanning electron microscope, and electrochemical corrosion studies. The in‐situ tethering and homogeneous dispersion of inorganic moiety in nanoregime throughout the TP system further enhances the stability, wettability, and corrosion protection ability of the nanohybrid vegetable oil‐based coating under corrosive environment. High phase angle value at higher frequency end indicates the stability of the coating system. Such coating systems composed of sustainable resource with improved mechanical, thermal, and corrosion protective properties have great potential in future 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".