Molecular Selectivity and Immiscibility During the Crystallization of Mixtures of a Set of Homologous Self-Assembling Molecules
Bibliographic record
Abstract
Utilizing self-assembly to create supramolecular structures is an active area at this time. Hybrid materials created by blending or doping, e.g., organic/inorganic or donor/acceptor complexes are of great interest in the design of novel materials systems. The effect of mixing of any two self-assembling molecules to modify the properties and to understand if the process of blending changes the nature of the self-assembly would be of interest. We discuss here the effect of blending of two (hydrogen bond mediated) self-assembling homologous molecules on the structure and morphology. Materials that are candidate vehicles for phase-change inkjet technology, biscarbamates with alkyl side chains, are chosen for this study. Thermal analysis and IR spectra indicate that, when two biscarbamates differing only in the length of the alkyl chain are blended, the two components are immiscible, although they are chemically similar. There is no intercalation of the alkyl chains and cocrystallization. They are thus an example of a self-sorting system. The extent of hydrogen bonding and the packing of the alkyl chains are not affected. However, each serve as a nucleating agent and reduce the size of the spherulites and crystallinity. The spherulitic growth rate decreases upon blending. Partial melting experiments show that the spherulites of each component do not form independently, but are intermixed, implying that one acts as the nucleating sites for the other. Thus, although these are self-sorting, the components in the mixture affect the morphology of each other upon crystallization. The behavior of this small molecule mixture is compared with those of hydrogen-bonded polymer blends. Studies of this nature on blends of self-assembling molecules are expected to be important in materials design for optimizing properties.
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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) | 0.000 | 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".