Microfluidic Mixing Through Sequential Sample Injection With Rapid Expansion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A novel micromixing strategy is presented which exploits axial diffusion of a continuous sequence of discrete samples in a microchannel expansion. Mixing of a continuous sequence in an electroosmotic flow through a sudden expansion region is modelled first assuming an ideal, square-wave injection. Different expansion geometries are examined as well as different sample lengths in order to determine the potential effectiveness of the mixing technique. To facilitate sequential injection on-chip, a new injection scheme is developed. The two outputs from the injector and an expansion region are integrated into a sequential injector micromixer chip design. Results for the sequential injection micromixer demonstrate rapid axial mixing of the individual stream sequences. However, cross-stream gradients in the output channel develop due to an inherent bias in the injection technique. Microchannel configurations that mitigate this bias were presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it