Use of (Super)Hydrophobic Surfaces in Digital Microfluidics
Bibliographic record
Abstract
A superhydrophobic (SH) surface is characterized by a water contact angle of >150 and a sliding angle <10. The water fearing properties result from significantly stronger cohesive forces of the resting liquid compared to weak adhesive forces with the surface material. Microfluidics is a discipline in which minute liquid volumes (10–9 to 10–18 litres) are actuated, mixed, merged, split, and/or analyzed on uniquely engineered devices. SH surfaces have aided digital microfluidics by facilitating magnetic actuation of droplets and the spontaneous formation of droplet microarrays. SH surfaces offer low friction between a liquid droplet and the surface itself, allowing for actuation using minimal force. Magnetically susceptible material (paramagnetic salts or superparamagnetic particles) can be added to the droplet, making it possible to manipulate the liquid droplet with an external magnetic field. \nThis thesis focuses on the magnetic actuation performance of aqueous droplets on different SH coatings including Ultra-Ever Dry, (a commercial coating), fluorine-containing and more environmentally friendly “fluorine-free” SH porous polymer monolith (PPM). Droplet kinematic parameters are explored (e.g. volume, acceleration/deceleration, particle concentration etc.) SH surfaces can be patterned with hydrophilic regions to create surface energy traps (SETs). In this way, the liquid can be pinned to the SETs for small volume deposition and droplet anchoring, respectively. We utilize the contrasting wetting behavior to conduct a droplet-based quantitative DNA assay using fluorescence detection. Furthermore, we examine the use of patterned hydrophobic PPM surfaces to conduct an ice recrystallization inhibition assay that allows the side-by-side comparison of up to a dozen samples treated in an identical, higher throughput manner. A novel method of droplet manipulation is explored termed biologically-driven magnetic actuation (BDMA), which uses magnetotactic bacteria (MTB). BMDA is used to transport droplets along various trajectories (e.g. square and eight-shaped tracks). We further demonstrate the use of BMDA for sequential merging and mixing of multiple droplets. SH surfaces are typically limited to aqueous droplet manipulation.\tAlternatively, slippery liquid-infused porous (SLIPS) surfaces have been shown to exhibit low friction for both organic and aqueous droplets. We demonstrate the magnetic actuation of aqueous and organic (hexadecane) droplets on SLIPS using paramagnetic particles. The sixth chapter of the thesis demonstrates the proof of principal application involving functionalized superparamagnetic particles for the extraction of asphaltenes from crude oil on omniphobic surfaces. This thesis successfully explains different ways (super)hydrophobic and SLIPS surfaces can be used for performing different DMF operations on aqueous and organic droplets.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".