Aggregation-Induced Energy Transfer in Color-Tunable Multiblock Bottlebrush Nanofibers
Bibliographic record
Abstract
The synthesis of multicomponent nanoscale structures with precisely addressable function is critical to the discovery of both new phenomena and new applications in nanotechnology. Though self-assembly offers low-cost routes to many such materials, these methods often require building blocks with particular structural motifs, thus limiting the scope of nanomaterials that can be prepared in these ways. Herein we use a bottom-up approach based on covalent chemistry to synthesize a series of bottlebrush copolymers from red, green, and blue luminescent macromonomers, which were then used to prepare multiblock organic nanofibers structurally analogous to nanoscale RGB pixels. Efficient energy transfer from a blue fluorophore to red and green phosphors can be modulated, using the solvent polarity as a stimulus, to give aggregation-induced changes in emission color. Aggregation was also accompanied by changes in the emission lifetime of the nanofiber from the nanosecond to microsecond regime. Additionally, changes in energy transfer efficiency and interchromophore distance were quantified using a FRET model. Preliminary demonstration of these materials as polarity-sensitive inks for encryption and encoding were also demonstrated using a red/blue fluorescence switch upon exposure to solvent. Finally, the potential complexity of optoelectronic materials accessible with these methods was demonstrated by combining these building blocks with charge-transporting materials to give organic nanofibers with ordered structures mimicking that of multilayer white OLEDs. Ultimately this work describes the preparation of robust, multicomponent nanofibers from general building blocks, combining their optoelectronic properties in ways that can be both reversibly switched and temporally resolved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".