Propagation of nanosecond discharge in an air gap containing a water droplet: modelling and comparison with time-resolved images
Bibliographic record
Abstract
Abstract The plasma-water interface is a complex medium characterized by interesting physical and chemical phenomena useful for many applications such as water processing or material synthesis. In this context, optimizing the transport of reactive species from plasma to water is crucial, and it may be achieved by increasing the surface-to-volume ratio of the processed object. Herein, we study the characteristics of a streamer produced by nanosecond discharge in air gap with a droplet of deionized water. The discharge is characterized experimentally by electrical measurements as well as by 1 ns-intergated ICCD images. To report plasma properties that are not accessible through experiment, such as the spatio-temporal evolution of electron density, electric field, and space charge density, a 2D fluid model is developed and adapted to the experimental geometry. Due to the fast propagation of the ionization front, the droplet is considered as a solid dielectric. The model solves Poisson’s equation as well as the drift-diffusion equation for electrons, positive ions, and negative ions. The utilized transport coefficients are tabulated as a function of the reduced electric field. Helmholtz equations are also included in the model to account for photoionization. The electron impact ionization source obtained from the model is compared to experimental 1 ns-integrated ICCD images, and a good agreement is observed. Finally, the model is used to investigate the influence of droplet dielectric permittivity and wetting angle (the angle between a liquid surface and a solid surface) on the properties of the discharge. Overall, the data reported herein demonstrate that the model can be used to investigate plasma properties under different conditions.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".