Transport and Self-Breakup of Drops for On-Chip Microfluidics
Bibliographic record
Abstract
We report a microfluidic transport technique which divides a given small volume of liquid into equal portions with no external input after the drop has been deposited on a surface. By branching of hydrophobic restrictions, we have achieved the surface analogue of a piping system. A symmetry in the drop front wetted perimeter allows near equal volume divisions. The use of discrete drops allows manipulation hence greater flexibility. Dilution of analyte is prevented and any projected kinetics may occur unhindered by the fluid transport. Implementation of on-chip systems are more practical since the device does not require power and can be made re-usable. This study illustrates that at least 3 divisions can be performed sequentially on an 1.5 µL volume to effect near equal final volumes of approximately 180 nL. A division of carrier liquid volume by 1/23 enables multiple analysis on separate stations in one Lab-on-a-chip application.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".