Induced charge electro-osmotic concentration gradient generator
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
Biomolecule gradients play an important role in the understanding of various biological processes. Typically, biological cells are exposed to linear and nonlinear concentration gradients and their response is studied for understanding cell growth, cell migration, and cell differentiation mechanisms. Recent studies have demonstrated the use of microfluidic devices for precise and stable concentration gradient generation. However, most of the reported devices are geometrically complex and lack dynamic controllability. In this work, a novel microfluidic gradient generator is presented which utilizes the induced charge electro-osmosis (ICEO) by introducing conducting obstacle in the microchannel. With the ICEO flow component, significant transverse convection can be generated within the microchannel, which can, in turn, be used to create nonlinear as well as asymmetric gradients. The characteristics of the developed concentration gradient are dependent on the interplay between fixed charge electro-osmotic and ICEO flows. It is shown that the proposed device can switch between linear and nonlinear gradients by just altering the applied electric field. Finally, the formation of user-defined concentration profiles (linear, convex, and concave) is demonstrated by varying the conducting obstacle size.
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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