Manipulation and Deposition of Complex, Functional Block Copolymer Nanostructures Using Optical Tweezers
Bibliographic record
Abstract
Block copolymer self-assembly has enabled the creation of a range of solution-phase nanostructures with applications from optoelectronics and biomedicine to catalysis. However, to incorporate such materials into devices a method that facilitates their precise manipulation and deposition is desirable. Herein we describe how optical tweezers can be used to trap, manipulate, and pattern individual cylindrical micelles and larger hybrid micellar materials. Through the combination of TIRF imaging and optical trapping we can precisely control the three-dimensional motion of individual cylindrical block copolymer micelles in solution, enabling the creation of customizable arrays. We also demonstrate that dynamic holographic assembly enables the creation of ordered customizable arrays of complex hybrid block copolymer structures. By creating a program which automatically identifies, traps, and then deposits multiple assemblies simultaneously we have been able to dramatically speed up this normally slow process, enabling the fabrication of arrays of hybrid structures containing hundreds of assemblies in minutes rather than hours.
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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".