A combined numerical and experimental investigation of droplet transportin solution Precursor Plasma Spray Process (SPPS)
Bibliographic record
Abstract
The Solution Precursors Plasma Spray (SPPS) is an emerging thermal spray process that utilizes a solution as a liquid feedstock suitable for the deposition of sub-micron-sized particles for applications in thermal barrier coatings and super-icephobic coatings.During the SPPS process, the droplet undergoes several thermo-physical stages, including an aerodynamic breakup, solvent vaporization, and precipitation of the dissolved solute to form a particle.Several parameters such as droplet size, solute concentration, thermophysical characteristics of the precursor, velocity, and temperature field of plasma affect the final morphology of the particle forming the coatings.In this study, droplets are composed of zirconium acetate as the solute dissolved in a mixture of water and ethanol.To address the challenging problem of particle morphologies by SPPS, the present work develops a numerical approach to model solvent evaporation and shell formation based on coupled heat and mass transfer equations within a single droplet in a plasma field.Subsequently, the calculated shell thickness is validated against a carefully designed experiment in a radio frequency plasma reactor using a droplet generator.Additionally, the effects of different heating rates, droplet size, and residence time on particle morphology are investigated, paving the way for a better understanding of SPPS.
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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".