Self-generated exclusion zone in a dead-end pore microfluidic channel
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
Particles can be manipulated by gradients of concentration (diffusiophoresis) and electric potential (electrophoresis) to transport them to desired locations. To establish these gradients, external stimuli are usually required. In this work, we manipulate particles through a self-generated concentration gradient within a PDMS-based microfluidic platform, without directly applying an external field. The interfacial chemistry of the PDMS results in a local increase of hydronium ions, leading to a concentration and electrical potential gradient in the system, which in turn generate a temporary exclusion zone at the pore entrance, extending up to half of the main channel, or 150 μm. With time, this exclusion zone diminishes as equilibrium in the ion concentration is reached. We study the dynamics of the exclusion zone thickness and find that the Sherwood number determines the size and stability of the exclusion zone. Our work shows, that even without introducing external ionic gradients, particle diffusiophoresis is significant in lab-on-a-chip systems. The interfacial chemistry of the microfluidic platform can have a significant influence on particle movement and this should be considered when designing experiments on diffusiophoresis. The observed phenomenon can be employed to design lab-on-a-chip-based sorting of colloidal particles.
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