Influence of Geometry and Surrounding Conditions on Fluid Flow in Paper-Based Devices
Bibliographic record
Abstract
Fluid flow behaviour in paper is of increasing interest due to the advantages and expanding use of microfluidic paper-based analytical devices (known as µPADs). Applications are expanding from those which often have low sample fluid volumes, such as diagnostic testing, to those with an abundance of sample fluid, such as water quality testing. The rapid development of enhanced features in μPADs, along with a need for increased sensitivity and specificity in the embedded chemistry requires understanding the passively-driven fluid motion in paper to enable precise control and consistency of the devices. It is particularly important to understand the influence of parameters associated with larger fluid volumes and to quantify their impact. Here, we experimentally investigate the impacts of several properties during imbibition in paper, including geometry (larger width and length) and the surrounding conditions (humidity and temperature) using abundant fluid reservoirs. Fluid flow velocity in paper was found to vary with temperature and width, but not with length of the paper strip and humidity for the conditions we tested. We observed substantial post-wetting flow for paper strips in contact with a large fluid reservoir.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".