Controlled Self-Assembly of Quantum Dot−Block Copolymer Colloids in Multiphase Microfluidic Reactors
Bibliographic record
Abstract
The controlled self-assembly of large compound quantum dot micelles (QDCMs), consisting of constituents of polymer-stabilized quantum dots (QDs) and amphiphilic polystyrene-b-poly(acrylic acid) stabilizing chains, in gas-liquid segmented microfluidic reactors is demonstrated. Self-assembly is initiated by fast mixing of water with the polymer constituents via chaotic advection, as liquid plugs containing reactants move through a sinusoidal mixing channel. The resulting QDCMs are then processed within a postformation channel, where circulating flow patterns develop within the liquid plugs, followed by off-chip quenching and analysis by transmission electron microscopy (TEM). Particle processing via circulating flow is found to involve a combination of particle growth via collision-induced coalescence and shear-induced particle breakup. The final mean QDCM sizes represent kinetic states arising from the competition between these two mechanisms, depending on tunable chemical and flow parameters. A systematic investigation of the experimental variables that influence particle size and polydispersity, including water concentration, flow rate, and the gas-to-liquid flow ratio, is conducted, demonstrating tunability of QDCM sizes in the range of approximately 40-140 nm. The importance of shear-induced particle breakup in the limit of high shear is illustrated by a common minimum particle size, 41 +/- 1 nm, which is achieved for all water contents by increasing the total flow rate to sufficiently high values.
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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 | 0.001 |
| 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 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".