Use of Block Copolymer-Stabilized Cadmium Sulfide Quantum Dots as Novel Tracers for Laser Scanning Confocal Fluorescence Imaging of Blend Morphology in Polystyrene/Poly(methyl methacrylate) Films
Bibliographic record
Abstract
This paper describes the first use of polymer-coated quantum dots (QDs) as fluorescent tracers for LSCFM imaging of phase morphology in polymer blends. Cadmium sulfide (CdS) QDs stabilized at the surface with a PS-b-PAA block copolymer are shown to be well dispersed via their polystyrene (PS) brush layer in the PS phase of solvent-cast 40/60 (w/w) PS/PMMA blends. The QDs are excluded from the PMMA phase, providing excellent fluorescence contrast for LSCFM imaging of the phase-separated blends. The presence of PS-b-PAA-stabilized QDs does not appear to affect the blend morphology, since the observed morphologies are the same when the percentage of QDs within the PS phase is varied from 10 to 50 wt %. These QD fluorescent tracers are used to characterize several aspects of blend morphology in solvent-cast 40/60 PS/PMMA blends containing PS homopolymer with either 100 (low molecular weight) or 1250 (high molecular weight) repeat units. In the PS(1250)/PMMA blends, a percolating distribution of PMMA droplets (2-25 mum) in a PS matrix is observed in the bulk, and a distinct inversion in the continuous phase is found near the glass substrate. In the PS(100)/PMMA blends, a "phase-in-phase" morphology is found, consisting of large PS domains (20-100 mum) dispersed in a PMMA continuous phase and small PMMA domains (1-2 mum) scattered throughout the larger PS droplets. The observed change in blend structure is attributed to a lower interfacial tension for the lower molecular weight PS.
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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) | 0.000 | 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 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".