Low Molecular Weight Organogels Based on Long-Chain Carbamates
Bibliographic record
Abstract
Thermoreversible organogels were prepared from carbamates with alkyl side chains of different lengths. Gelation was possible only up to an alkyl side chain length of 12 carbons, beyond which crystallization occurs, due to the dominant van der Waals interaction between the alkyl chains. This is in contrast to other alkane-based organogels, in which gelating efficiency increased with the length of the alkane chain (see Abdallah, D. J.; Weiss, R. G. Adv. Mater. 2000, 12, 1237). The critical concentration for gelation decreases drastically with an increase in the side chain length. Xerogels of these show birefringent fibers with uniform cross section and unlimited growth in one direction. The extent of this unlimited growth is affected by the length of the alkyl side chain in the carbamate, which finally ceases the gel formation ability of the carbamate. Cryogenic scanning electron microscopy images of the gels are similar to those of xerogels. From X-ray diffraction of the fibers, we propose that the growth direction is along the plane of hydrogen bonds between the carbamate molecules. The thickness of the fibers depends on the length of the alkyl side chain. Morphological differences are seen between gels prepared by slow cooling and quenching of the solution. Thus, the morphology of the fibrous xerogels of the carbamates can be tailored for specific applications, by the choice of the alkyl side chain length and the rate of cooling the solution.
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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".