Microfluidic Manufacturing of Polymeric Nanoparticles: Comparing Flow Control of Multiscale Structure in Single-Phase Staggered Herringbone and Two-Phase Reactors
Bibliographic record
Abstract
We compare the microfluidic manufacturing of polycaprolactone-block-poly(ethylene oxide) (PCL-b-PEO) nanoparticles (NPs) in a single-phase staggered herringbone (SHB) mixer and in a two-phase gas-liquid segmented mixer. NPs generated from two different copolymer compositions in both reactors and at three different flow rates, along with NPs generated using a conventional bulk method, are compared with respect to morphologies, dimensions, and internal crystallinities. Our work, the first direct comparison between alternate microfluidic NP synthesis methods, shows three key findings: (i) NP morphologies and dimensions produced in the bulk are different from those produced in a microfluidic mixer, whereas NP crystallinities produced in the bulk and in the SHB mixer are similar; (ii) NP morphologies, dimensions, and crystallinities produced in the single-phase SHB and two-phase mixers at the lowest flow rate are similar; and (iii) NP morphologies, dimensions, and crystallinities change with flow rate in the two-phase mixer but not in the single-phase SHB mixer. These findings provide new insights into the relative roles of mixing and shear in the formation and flow-directed processing of polymeric NPs in microfluidics, informing future reactor designs for manufacturing NPs of low polydispersity and controlled multiscale structure and function.
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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 | 0.000 | 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".