Bibliographic record
Abstract
Digital microfluidics is a new technology that permits manipulation of liquid droplets on an array of electrodes. Using this technology, nanoliter to microliter size droplets of different samples and reagents can be dispensed from reservoirs, moved, split, and merged together. Digital microfluidics is poised to become an important and useful tool for biomedical applications because of its capacity to precisely and automatically carry out sequential chemical reactions. In this thesis, a set of tools is presented to accelerate the integration of digital microfluidics into Lab-on-a-Chip platforms for a wide range of applications.\nAn important contribution in this thesis is the development of three rapid prototyping techniques, including the use of laser printing to pattern flexible printed circuit board (PCB) substrates, to make the technology accessible and less expensive. Using these techniques, both digital and channel microfluidic devices can be produced in less than 30 minutes at a minimal cost. These rapid prototyping techniques led to a new method for manipulating liquid droplets on non-planar surfaces. The method, called All Terrain Droplet Actuation (ATDA), was used for several applications, including DNA enrichment by liquid-liquid extraction. ATDA has great potential for the integration of different physico-chemical environments on Lab-on-a-Chip devices.\nA second important contribution described herein is the development of a new microfluidic format, hybrid microfluidics, which combines digital and channel microfluidics on the same platform. The new hybrid device architecture was used to perform biological sample processing (e.g. enzymatic digestion and fluorescent labeling) followed by electrophoretic separation of the analytes. This new format will facilitate complete automation of Lab-on-a-Chip devices and will eliminate the need for extensive manual sample processing (e.g. pipetting) or expensive robotic stations.\nFinally, numerical modeling of droplet actuation on single-plate digital microfluidic devices, using electrodynamics, was used to evaluate the droplet actuation forces. Modeling results were verified experimentally using an innovative technique that estimates actuation forces based on resistive forces against droplet motion. The results suggested a list of design tips to produce better devices. It is hoped that the work presented in this thesis will help introduce digital microfluidics to many of the existing Lab-on-a-Chip applications and inspire the development of new ones.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".