Enhanced Evaporation of Microscale Droplets With an Infrared Laser
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Enhancement of water droplet evaporation by added infrared radiation was modeled and studied experimentally in a vertical laminar flow channel. Experiments were conducted on droplets with nominal initial diameters of 50 μm in air with relative humidities ranging from 0% to 90% RH. A 2800 nm laser was used with radiant flux densities as high as 4 × 105 W/m2. Droplet size as a function of time was measured by a shadowgraph technique. The model assumed quasi-steady behavior, a low Biot number liquid phase, and constant gas–vapor phase material properties, while the experimental results were required for model validation and calibration. For radiant flux densities less than 104 W/m2, droplet evaporation rates remained essentially constant over their full evaporation, but at rates up to 10% higher than for the no radiation case. At higher radiant flux density, the surface-area change with time became progressively more nonlinear, indicating that the radiation had diminished effects on evaporation as the size of the droplets decreased. The drying time for a 50 μm water droplet was an order of magnitude faster when comparing the 106 W/m2 case to the no radiation case. The model was used to estimate the droplet temperature. Between 104 and 5 × 105 W/m2, the droplet temperature changed from being below to above the environment temperature. Thus, the direction of conduction between the droplet and the environment also changed. The proposed model was able to predict the changing evaporation rates for droplets exposed to radiation for ambient conditions varying from dry air to 90% relative humidity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it