Dynamics of Drops as Confined Systems Containing Nanoparticles-Reformation of Nanoparticles and Evaporation of Water
Bibliographic record
Abstract
Brine is used to displace crude oil in a reservoir and its performance improves when brine contains nanoparticles.It is the presence of nanoparticles in confinements, such as at dynamic contact lines and in thin films, which is of importance.The investigators here have determined a fast way to obtain confined systems by evaporating a small drop of water containing nanoparticles.Water droplets containing nanoparticles of alumina or silica were evaporated on surfaces of polyethylene terephthalate sheets, which are partially wet by water, and glass which is fully wet.After the liquid in the drops evaporated, the residues were examined under a microscope and sintering and melting effects, crystals growth and dendritic formations for alumina and monoliths for silica were seen.The coffee stains are seen in most cases; however measurements show that the contact lines are not always pinned.Turbidity measurements showed that no significant reformation could have taken place in the bulk liquid.A simple model for evaporation, based on geometric measurements, showed that much of the film seen on the solid arose out of evaporation of water that forced the particles down.Sintering rates into the interior could be quantified and shown to be unstable.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".