Experimental Study of Particle-Liquid Flow Behaviour in a Microchannel Attached to an Inlet Reservoir
Bibliographic record
Abstract
An experimental study of a solid particle-liquid mixture in a microchannel was conducted by injecting a particle-liquid mixture into a 3.0 mm diameter cylindrical reservoir connected to a square microchannel. Glass particles with diameters ranging from 8 to 12 μm and density between 0.95 and 1.15g/ml, as well as polystyrene particles with diameters ranging from 8 to 50μm and an average density of 1.03–1.05 g/ml were mixed with de-ionized water to create particle-liquid mixtures. The mixture could be continuously stirred in the reservoir using a small magnetic stir bar. The number of particles entering the microchannel was found to depend on the concentration and density of the particles in the reservoir, stirring and fluid flow rates. The particles with a density larger than the carrier fluid entered the microchannel, settled at the bottom of the channel and became immobile at low fluid flow rates, blocking the subsequent particle flow. In many cases, the particles flowed in small groups or clusters, which were separated by short distances. The average distance between the particles or particle clusters was found to vary both with the stirring rate in the reservoir as well as the fluid flow rate in the microchannel.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".