A New Approach to Polymorphism in Molecular Crystals: Substrate‐Mediated Structures Revealed by Lattice Phonon Dynamics
Bibliographic record
Abstract
Abstract The issue of polymorphism in molecular crystals is discussed, taking into account the substrate‐mediated structures, that is, structures grown at the interface of different substrates. Bulk and thin films of a compound both share the potentiality to display different crystal forms. However, unlike bulk polymorphs, whose structures are determined by their different molecular packing, thin film structures depend very much on the molecular organization of the organic layers on the substrate, which may, or may not, lead to an ordered structure, depending on the nature of the interface and on the growth conditions. Based on large part in some of the authors’ recent works, these thin film structures are classified as distorted bulk, substrate‐selected and substrate‐stabilized polymorphs, with some subtle differences which may yield a polymorph to belong not exclusively to a single one of these categories. Some experiments are then focused upon, involving charge transport at the interface, as well as how far the effect of the surface goes. Furthermore, the authors comment on how the surface‐mediated structures evolve to the single crystal phase in the cases of pentacene and α‐sexithiophene. Finally, the transition from a 3‐ to a 2D regime of growth is shortly discussed in terms of low‐dimensional disorder.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".