Controlling the assembly of hydrogen-bonded supramolecular polymers by the strategy of molecular tectonics
Bibliographic record
Abstract
Abstract Studies of how hydrogen bonding can be used to control molecular association continue to yield exciting discoveries in supramolecular chemistry. A simple way to make molecules that associate predictably is to link carefully selected cores to functional groups that form multiple hydrogen bonds according to reliable patterns. Bifunctional molecules constructed according to this strategy can associate to form linear aggregates robust enough to warrant the name supramolecular polymers, even though the bifunctional monomers are joined only by hydrogen bonds. More complex molecules with multiple hydrogen-bonding sites can be devised so that neighbors are held in predetermined positions, giving crystalline solids with predictable architectures and properties not previously seen in other materials. Initial studies of the ability of such compounds to associate in solution and in the molten state suggest that hydrogen-bonded networks can be purposefully designed to create novel par- tially ordered liquid materials, including liquid crystals, gels, and fluids with unusual rheological properties.
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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".