Co‐Assembly and Self‐Sorting Effects in Gels of Blends of Polyurethane Model Compounds
Bibliographic record
Abstract
Abstract We present studies on two‐component organo‐gels of small molecule analogues of polyurethanes. Whereas the two‐component organo‐ or polymer gels reported in the literature so far involve two types of polymers or polymer/ small molecules, this paper deals with blends of homologous pairs of biscarbamates, which differ only in the number of CH 2 groups in the side chain. The mixture of any two biscarbamates self‐sort when crystallized from the melt or solution. We also showed before that these molecules, with a side chain shorter than (CH 2 ) 6 do not form gels by themselves as a single component. However, in this work, it was found that a blend of biscarbamates with side chains (CH 2 ) 3 and (CH 2 ) 15 (denoted as C 3 / C 15 henceforth) formed a homogeneous gel with benzonitrile as the solvent. A small ratio of the C 15 component is sufficient to depress the precipitation of C 3 and form a gel, leading to co‐assembly in these gels. Such an effect was also seen in the gelation of blends of C 8 and C 9 , which differ by just one CH 2 group in the side chains ( Δx =1). With the gels of C 7 /C 9 blends ( Δx =2), an ageing effect was seen in that the as‐prepared gel did not show any self‐sorting, but the aged gel did. Self‐sorting was observed in the two‐component gels of biscarbamates with Δx > 2. We believe that this is the first case of two‐component organo‐gels of homologous pairs in which co‐assembly and self‐sorting phenomena were observed.
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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".