Frustrated 2D Molecular Crystallization
Bibliographic record
Abstract
Grafting isophthalic acid groups to linear connectors produces tetracarboxylic acids 2 − 4, which are extended analogues of trimesic acid ( 1 ). Normal pairwise association of -COOH groups induces trimesic acid to form a hexagonal network held together by six hydrogen bonds per molecule. In contrast, analogues 2 − 4 are designed to form two polymorphs, parallel network II and Kagomé network III, which are linked by eight hydrogen bonds per molecule. The particular connectivity of these networks allows a smooth transition from one to the other without introducing discontinuities in hydrogen bonding. DFT calculations suggest that subtle differences in hydrogen bonding favor parallel motif II for short tetraacid 2 and Kagomé motif III for long tetraacid 4, whereas the two motifs are closely similar in energy for intermediate tetraacid 3 . These preferences were confirmed by using STM to image the adsorption of compounds 2 − 4 on graphite. 2D crystallization of tetraacid 3 is frustrated, presumably because the two motifs are matched in energy and can merge smoothly. Nevertheless, adsorption of compound 3 shows a high degree of order, and most molecules have specific orientations relative to their neighbors, as dictated by motifs II and III . Such assemblies reveal the structure of a locally ordered 2D molecular glass, and they offer guidelines for the design of new aperiodic molecular materials.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".