Comparing classical electrodynamic theories predicting deformation of a water droplet in a tightly focused Gaussian beam
Bibliographic record
Abstract
Optical forces are used to accelerate and trap water droplets in applications such as remote spectroscopy and noninvasive surgery. However, the microscopic deformation of droplets is difficult to predict. In this work, the local electrodynamic impulse imparted by a focused laser beam to a water droplet is numerically modeled via a simulation that invokes intensive conservation of electrodynamic and kinetic momentum. Electrodynamic momentum is modeled locally using a D3Q7 electrodynamic lattice-Boltzmann method, and kinetic momentum is modeled locally using a multi-phase D3Q27 weighted-orthogonal lattice-Boltzmann method. Six different electrodynamic theories are implemented in the simulation domain predicting three unique types of droplet dynamics driven by differences in the direction and distribution of force density. The unique water droplet morphology affects the center-of-mass acceleration of the droplet. This study suggests that empirical measurement of the light-driven acceleration of a droplet may help to validate a single electrodynamic theory.
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 | 0.001 |
| 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 | 0.001 | 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".