Effects of Hydrophobic Recovery of Plasma Treated PDMS Microchannels on Surface Tension Driven Flow
Bibliographic record
Abstract
Surface tension driven flow is used in numerous microfluidic applications. It is considered a passive pumping technique which doesn’t require any external energy, aside from the interfacial surface energy between the fluid and walls. Thus, it is preferred in applications where the goal is fluid and sample transport. In many applications PDMS (Polydimethylsiloxane) is the most adapted material for chip manufacturing in microfluidics. PDMS has several aspects that make it favorable for microfluidic applications. Ease of chip fabrication, cost effectiveness, chemical stability, and good optical properties are features offered by PDMS and desirable for microfluidics. On the other hand, PDMS has some shortcomings. One of importance is that PDMS is naturally hydrophobic. For this reason it is hard to achieve surface tension flow in native PDMS for various fluids used in microfluidics. Thus, native PDMS must be treated to get hydrophilic surface properties. The most used method for altering PDMS properties to a hydrophilic state is by plasma treatment. This treatment has several aspects where it enhances the attachment of PDMS to substrates, it alters the surface from a hydrophobic to a hydrophilic state, and it increases the electrokinetic properties of PDMS. As a result, after plasma treatment surface tension pumping can be achieved in PDMS, unlike native PDMS. However, plasma treatment is not permanent due to the diffusion of non-cured PDMS species to the surface of microchannels, as is well documented in the literature. The change of plasma treated PDMS with time will affect both the electrokinetic and surface tension driven flow. To our knowledge, researchers have quantitatively documented the time effect on plasma treated PDMS microchannels (aging of PDMS) for electrokinetic flow, but not for surface tension driven flow. Therefore, a quantitative examination of the time effect on surface tension driven flow for plasma treated PDMS gives valuable information on both regaining the hydrophobic properties in PDMS and changes in the passive flow conditions. In this work a quantitative study on the hydrophobic recovery for oxygen-plasma treated PDMS and its effects on surface tension flow was examined. The study was performed with a quantitative flow visualization technique (micro particle image velocimetry). It was found that the aging of PDMS will strongly affect surface tension flow of water based solutions in PDMS microchannels. This study gives important information on the effectiveness of surface tension driven flow for oxygen plasma treated PDMS microchannels.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".