“Smart” Self-Assembled Quantum Dots Regulate and Stabilize Structure in Phase-Separated Polymer Blends
Bibliographic record
Abstract
Cadmium sulfide (CdS) quantum dots (QDs) coated with mixed polystyrene (PS)/poly(methyl methacrylate) (PMMA) brush layers (PS/PMMA–CdS) self-assemble at the polymer/polymer interface of a phase-separating blend of the corresponding homopolymers, forming an encapsulating shell surrounding PMMA islands in a PS matrix. The segregated QDs regulate phase separation during spin-coating and dramatically stabilize the spin-coated blend morphologies during subsequent annealing, compared to neat PS:PMMA blends which undergo rapid phase inversion and coarsening. PS/PMMA–CdS QDs are shown to retain their photoluminescence following interfacial self-assembly and subsequent annealing. Free-standing arrays of polymer/QD rings formed via directed self-assembly can be developed by selective solvent washing and removal of homopolymers from the spin-coated films. This work demonstrates the principle that colloidal inorganic elements such as QDs, along with possessing interesting optical properties, can also play a key role in the self-organization and stability of polymer blend-based devices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".