Fabrication of Highly Porous Nonspherical Particles Using Stop-Flow Lithography and the Study of Their Optical Properties
Bibliographic record
Abstract
A microfluidic flow lithography approach was investigated to synthesize highly porous nonspherical particles and Janus particles in a one-step and high-throughput fashion. In this study, using common solvents as porogens, we were able to synthesize highly porous particles with different shapes using ultraviolet (UV) polymerization-induced phase separation in a microfluidic channel. We also studied the pore-forming process using operating parameters such as porogen type, porogen concentration, and UV intensity to tune the pore size and increase the pore size to submicron levels. By simply coflowing multiple streams in the microfluidic channel, we were able to create porous Janus particles; we showed that their anisotropic swelling/deswelling exhibit a unique optical shifting. The distinctive optical properties and the enlarged surface area of the highly porous particles can improve their performance in various applications such as optical sensors and drug loading.
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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".