Betulin Self‐Assembly: From High Axial Aspect Crystals to Hedgehog Suprastructures
Bibliographic record
Abstract
Abstract Betulin is introduced as a building block of supramolecular structures that form by noncovalent interactions. Betulin, an abundant triterpene, is first extracted from birch bark to self‐assemble into hierarchical crystalline structures. Following a direct bottom‐up process, solvatomorphs of betulin‐2‐propanol form high axial aspect microparticles, 100–300 µm in length, and lateral sizes in the 15–40 µm range. Under sonication, the microparticles evolve into 3D hedgehog suprastructures (15–30 µm in size) comprising a core (3–5 µm diameter) with connected spines (200–300 nm in width). Depending on the intensity of the delivered energy, the associated morphogenesis starts with metastable aggregates that undergo dislocation, solvent migration, and radial growth. It is found that the formed spherulite‐like, hedgehog structures are a consequence of residual solvent diffusion, leading to crystallites with oriented attachment on specific planes. These results add to the design of structures from natural building blocks, which are expected to deliver functions encoded in the respective morphology. Owing to the unique features of betulin supraparticles, they develop surface architectures, for instance, in superhydrophobic coatings, which are shown to exhibit exceptional repellency and surface mechanical strength, as tested on various substrates.
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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".