Vinylidene Fluoride-Based Polymer Network via Cross-Linking of Pendant Triethoxysilane Functionality for Potential Applications in Coatings
Bibliographic record
Abstract
Vinylidene fluoride (VDF)-based copolymers bearing pendant trialkoxysilane groups for potential applications for coatings were synthesized via a free radical copolymerization of VDF with functional 2-trifluoromethyl acrylate cyclic carbonate monomer (MAF-cyCB), followed by introduction of silane pendant groups. MAF-cyCB was prepared from 2-trifluoromethacrylic acid with 70% overall yield. Radical copolymerization of VDF with MAF-cyCB initiated by tert -amyl peroxy-2-ethylhexanoate at varying [VDF] 0 /[MAF-cyCB] 0 ratios led to several poly(VDF- co -MAF-cyCB) copolymers having different molar percentages of VDF (77–96%). The average molecular weights ( M n s) reached up to 19 000 g mol –1 in fair to good yields (45–74%). Compositions and microstructures of all synthesized copolymers were achieved by 1 H and 19 F NMR spectroscopies. The resulting poly(VDF- co -MAF-cyCB) copolymers exhibited moderately high melting temperature (131–161 °C, with respect to the VDF content) while the degree of crystallinity, which reached up to 34%, decreased with increasing MAF-cyCB. Then, the pendant cyclic carbonate ester groups of the synthesized poly(VDF- co -MAF-cyCB) copolymers were quantitatively converted into novel triethoxysilane-functionalized PVDF, which could be further hydrolyzed under acidic conditions into trihydroxysilane-functionalized PVDF. Finally, steel plates were coated with the silylated PVDF and displayed improved adhesion properties compared to those of pristine PVDF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".