Controlled Interfaces as Lab-on-a-chip Components
Bibliographic record
Abstract
This thesis is devoted to the study and application of controlled two-phase interfaces in the context of microfluidic and lab-on-a-chip systems. Spontaneous emergence and presence of unwanted gas-liquid interfaces (i.e. bubbles) in microfluidic devices are often problematic. In this thesis it is shown through experimentation, numerical, and analytical modeling that precisely controlled gas-liquid interfaces may be exploited as effective microfluidic components to perform functions such as valving, sampling and liquid routing within microfluidic devices or even manipulate layers of pulmonary cells to recapitulate alveolar function. Flow control strategies presented in this thesis include the bubble gate for valving and sampling and the bubble pump for liquid routing in microchannels. Flow control and actuation in the devised techniques are done by controlled gas bubbles and therefore, their function is independent of the elasticity of substrate material and requires only a single layer fabrication unlike the majority of available microfluidic flow control techniques. In this thesis, the application of controlled two-phase interfaces is further extended by introduction and characterization of a microfluidic tensiometer that can readily measure interfacial tension between pairs of immiscible fluids both gas-liquid and liquid-liquid. Additionally, it is shown that controlled gas-liquid interfaces within a surface modified capillary plate may be used as cell culture platforms for in vitro modeling of the alveolar epithelium function. In order to do so, it is investigated in this thesis whether pulmonary epithelial cells can be cultured atop a controlled air-liquid interface and form a confluent layer with functional tight junctions that can serve as a model for alveolar epithelium. Finally a number of further extensions and applications for the techniques developed in this thesis are presented in form of preliminary designs and calculation as groundwork for future continuation of this thesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".