The zeta potential of PMMA in contact with electrolytes of various conditions: Theoretical and experimental investigation
Bibliographic record
Abstract
Many unit operations required in microfluidics can be realised by electrokinetic phenomena. Electrokinetic phenomena are related to the presence of electrical surface charges of microfluidic substrates in contact with a liquid. As surface charges cannot be directly measured, the zeta potential is considered as the relevant parameter instead. PMMA is an attractive microfluidic substrate since micron-sized features can be manufactured at low costs. However, the existence of PMMA surface charges is not well understood and the zeta potential data found in the literature show significant disagreement. In this article, we present a thorough investigation on the zeta potential of PMMA. We use computations of the potential distribution in the electrical double layer to predict the influence of various electrolyte parameters. The generated knowledge is compared to extensive experiments where we investigate the influence of ionic strength, pH, temperature and the nature of the electrolyte. Our findings imply that two different mechanisms influence the zeta potential depending on the pH value. We propose pure shielding in the acidic and neutral milieus while adsorption of co-ions occurs along with shielding in the alkaline milieu.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".