Liquid Triarylamines: The Scope and Limitations of Piers–Rubinsztajn Conditions for Obtaining Triarylamine–Siloxane Hybrid Materials
Bibliographic record
Abstract
New liquid triarylamine-siloxane hybrid materials are produced using the Piers-Rubinsztajn reaction. Under mild conditions, liquid analogues of conventional and commonly crystalline triarylamines are easily synthesized from readily available or accessible intermediates. Using a diverse selection of triarylamines, we explored the effects of siloxane group and substitution pattern on the physical properties of these materials, and we have demonstrated that relatively large molecular liquids with desirable electrochemical properties can be produced. The interactions between the strongly Lewis acidic catalyst used for this transformation, tris(pentafluorophenyl)borane (BCF), and the Lewis basic triarylamine substrates were studied. Through UV-vis-NIR and (19)F NMR spectroscopy, we have proposed that the catalyst undergoes a reversible redox reaction with the substrates to produce a charge transfer complex. The formation of this charge transfer complex is sensitive to the oxidation potential of the triarylamine and can greatly affect the kinetics of the Piers-Rubinsztajn reaction.
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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".