Multifunctional amphiphilic siloxane architectures using sequential, metal‐free click ligations
Bibliographic record
Abstract
Abstract Polysiloxanes or silicones are a class of macromolecules widely used in commerce because of their exceptional properties. Their derivatization leads to functional silicones with added value and properties, such as surfactants and liquid crystals, among many others. However, most silicone surfactants are monofunctional, owing to the synthetic challenges associated with the introduction of multiple functional groups onto the hydrolytically sensitive siloxane backbone. Thus, general routes to surface active silicones with multiple and different functional groups are not available. Herein, a synthetic strategy is reported that permits sequential derivatization of silicones with hydrophiles including oligo(ethylene oxides), carboxylic acids, and bromoalkylesters using a simple metal‐free Click reaction: the process benefits from mild conditions, extremely high yields and does not generate any by‐products, allowing the facile preparation of di‐ and trifunctional silicones that could not be readily obtained using traditional methods. The products exhibit amphiphilic characteristics as demonstrated through interfacial tension measurements that yielded the critical aggregation concentration of selected compounds. © 2012 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2013
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) | 0.001 | 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 | 0.001 |
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".