Rapid fabrication of circular channel microfluidic flow‐focusing devices for hydrogel droplet generation
Bibliographic record
Abstract
A rapid method to fabricate a flow‐focusing microfluidic device with circular channels for droplet generation is presented. To create the desired ‘polydimethylsiloxane (PDMS)’ channel geometry, moulds using a rapid and cheap three dimensional (3D) printing process comparing with conventional microfabrication method have been fabricated. The 3D printer with a 16 μm layer resolution utilised to fabricate 100 μm half circular microfluidic moulds. The finished moulds were baked and silanized prior to casting to avoid the incomplete curing problem of the ‘PDMS’ castings. Casted ‘PDMS’ halves were aligned and bonded together to build complete microfluidic chips by an oxygen plasma treatment. Due to the resolution limitation of 3D printing, the channels were not perfectly circular rather than elliptical. A liquid ‘PDMS’ injection process was used and optimised to create fully circular channels, and also address challenges regarding the misalignment of the upper and lower halves of the microfluidic chip. Circular channels were successfully formed in the flow‐focusing microfluidic device through the post ‘PDMS’ injection process without any blockage of the cross junction. The device functioned well to create ∼200 μm droplets.
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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) | 0.001 | 0.001 |
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".