Emergent Self‐Assembly Pathways to Multidimensional Hierarchical Assemblies using a Hetero‐Seeding Approach
Bibliographic record
Abstract
The controlled formation of complex and functional 1-, 2-, and 3D hierarchical assemblies from molecular building blocks represents a key current challenge. Herein, we report the use of a seeded growth approach for a series of perylenediimide-based molecules (PDIs 1-4) to access otherwise inaccessible self-assembly pathways that yield complex hierarchical structures. The key to the new approach is to use hetero-seeds which possess a different composition and morphology from that of the molecular building block. For example, a nanotube seed (from PDI 3) and a microribbon seed (from PDI 4) were found to initiate different self-assembly pathways for PDI 1, which normally assembles to yield nanocoils. This led to the formation of unprecedented 3D scroll-like and scarf-like hierarchical nanostructures, respectively. Also, the hetero-seeds from PDI 3 initiate hidden self-assembly pathways of PDI 2 to generate 1D tubular heterojunctions. Significantly, this new strategy offers new opportunities to create emergent and functional hierarchical and complex structures from small molecule precursors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".