Fluoropolymers functionalized by phosphorous and silicon groups : syntheses, characterization and applications
Bibliographic record
Abstract
Fluorinated polymers are intresting macromolecules which due to their unique properties are often used in special applications in building industries, aerospace, chemical engineering, optics, textile treatment and microelectronics. This thesis focusses on the development of phosphorous and silane functional fluorinated polymers through the conventional radical co/terpolymerization of functional monomers with vinylidene difluoride (VDF). These functional monomers were prepared from the modification of 2-(Trifluoromethyl)acrylic acid (MAF) to prepare MAF-esters with the desired functional group. First a fundamental study regarding the kinetics of polymerization of VDF with MAF-TBE revealed that these monomer pair tends to cross propagate resulting in an alternating copolymer. Phosphonate functional MAF (MAF-DMP) was then prepared and its copolymerization with VDF led to phophonate functional PVDF, that after the consequent hydrolysis of the phosphonate group into phosphonic acid showed anticorrosion properties to steel. Following the same concept, a cyclic carbonate functional MAF monomer (MAF-cyCB) was also copolymerized with VDF. The cyclic carbonate groups in the obtained PVDF copolymer was then opened by aminopropyltriethoxysilane to introduce a silane group, that by its hydrolysis allowed the copolymer to adhere strongly onto substrates. Finally, a terpolymer based on PVDF functional with both a phosphonate and a triethoxysilane group is prepared. The silane group was then hydrolyzed and crosslinked to obtain a 3D network of polymers. Finally, the hydrolysis of the phosphonate group into phosphonic acid led to material that can be employed in Eu(III) ion extraction from water.
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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".