A Bubble‐Assisted Approach for Patterning Nanoscale Molecular Aggregates
Bibliographic record
Abstract
We demonstrate a new approach to pattern functional organic molecules with a template of foams, and achieve a resolution of sub 100 nm. The bubble-assisted assembly (BAA) process is consisted of two periods, including bubble evolution and molecular assembly, which are dominated by the Laplace pressure and molecular interactions, respectively. Using TPPS (meso-tetra(4-sulfonatophenyl) porphyrin), we systematically investigate the patterns and assembly behaviour in the bubble system with a series of characterizations, which show good uniformity in nanoscale resolution. Theoretical simulations reveal that TPPS's J-aggregates contribute to the ordered construction of molecular patterns. Finally, we propose an empirical rule for molecular patterning approach, that the surfactant and functional molecules should have the same type of charge in a two-component system. This approach exhibits promising feasibility to assemble molecular patterns at nanoscale resolution for micro/nano functional devices.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".