High‐Throughput Synthesis and Characterization of Aryl Silicones by Using the Piers–Rubinsztajn Reaction
Bibliographic record
Abstract
Arylsilicones are widely exploited for their thermal and optical properties. The creation of phenylsilicone elastomers with specific physical properties is typically done by a "one-off" formulation and test process. Herein, it is demonstrated that high-throughput synthesis methods can be used to rapidly prepare a series of arylsilicone elastomers and then the relative impact of different aryl groups on their physical properties is assessed. Aromatic groups were incorporated into polydimethylsiloxane (PDMS) elastomers by exploiting the relative reactivity of different functional groups in the Piers-Rubinsztajn reaction. To analyze trends in the silicone mechanical properties as a function of increasing aryl concentration-structure/property relationships-libraries of elastomers were both quickly synthesized and characterized by using high-throughput suites starting from low viscosity silicone oils/monomers in 96-well plates. Liquid handling parameters were optimized to effectively work with the silicones. Incorporating aryl instead of alkyl crosslinkers into the PDMS backbone increased the silicone elastomer modulus by approximately 50 % (at a crosslink density of 6 %); elastomers prepared with an aromatic crosslinker with three contact points led to much higher moduli compared with those with one contact point at the same crosslink density. When located at precise rather than random points on the silicone chains, diphenylsilicones had lower moduli than analogous monophenylsilicones.
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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 | 0.000 |
| 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 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".