Polymer Dots with Enhanced Photostability, Quantum Yield, and Two-Photon Cross-Section using Structurally Constrained Deep-Blue Fluorophores
Bibliographic record
Abstract
Semiconducting polymer dots (Pdots) have emerged as versatile probes for bioanalysis and imaging at the single-particle level. Despite their utility in multiplexed analysis, deep blue Pdots remain rare due to their need for high-energy excitation and sensitivity to photobleaching. Here, we describe the design of deep blue fluorophores using structural constraints to improve resistance to photobleaching, two-photon absorption cross sections, and fluorescence quantum yields using the hexamethylazatriangulene motif. Scanning tunneling microscopy was used to characterize the electronic structure of these chromophores on the atomic scale as well as their intrinsic stability. The most promising fluorophore was functionalized with a polymerizable acrylate handle and used to give deep-blue fluorescent acrylic polymers with Mn > 18 kDa and Đ < 1.2. Nanoprecipitation with amphiphilic polystyrene-graft-(carboxylate-terminated poly(ethylene glycol)) gave water-soluble Pdots with blue fluorescence, quantum yields of 0.81, and molar absorption coefficients of (4 ± 2) × 108 M–1 cm–1. This high brightness facilitated single-particle visualization with dramatically improved signal-to-noise ratio and photobleaching resistance versus an unencapsulated dye. The Pdots were then conjugated with antibodies for immunolabeling of SK-BR3 human breast cancer cells, which were imaged using deep blue fluorescence in both one- and two-photon excitation modes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".