Kinematic Viscosities of High‐Temperature Materials Used in Plasma Spraying
Bibliographic record
Abstract
A simple analytical model based on the law of conservation of energy was developed to estimate the kinematic viscosity of high‐temperature materials. An energy balance between the kinetic, viscous dissipation, and surface energies of high‐speed molten droplets and the splats formed after impact and spreading was conducted to produce a nondimensional relationship between kinematic viscosity and the maximum spread factor of the splat. The dimensional kinematic viscosities of a wide variety of high‐temperature materials were determined and comparisons with experimentally measured viscosities were conducted. It was found that the predictions of the model agreed to within one order‐of‐magnitude of experimentally measured values. Experimental data for high‐temperature ceramics such as yttria‐stabilized zirconia were unavailable for comparison. However, the agreement between the model and experimental values of kinematic viscosity observed for alumina, coupled with the monoclinic fluorite structure and high density of zirconia, suggested that its kinematic viscosity was probably much lower than that of alumina, as predicted by the analytical model.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".