Investigation of Capillary Filling Dynamics of Multicomponent Fluids in Straight and Periodically Constricted Microchannels
Bibliographic record
Abstract
An extensive study of capillary flow of fluids with various viscosities in straight and periodically constricted microchannels with different surface wettability is presented. Capillary filling speed in hydrophilic, less hydrophilic, and hydrophobic microchannels were experimentally monitored and compared with the Washburn theoretical model. For all liquids, a linear relationship was found between the square of propagation distance and time, which is expected for Newtonian fluids. Experimental results indicated slower velocity compared to the theoretical prediction due to simplifications of the Washburn model. Capillary filling speed of fluids into long-fluororinated chain silane modified channels confirmed the expected lyophobic nature of the coating (i.e., not favorable for either hydrophilic or hydrophobic liquids). Presence of the precursor film ahead of the three-phase contact line in the microscopic level was demonstrated. White light and fluorescent images confirmed the presence of precursor film and capillary evaporation at the interface. Evaporation enhanced the deviation between experimental and theoretical results due to continuous wettability alteration of penetrating fluid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".