Rheological Behavior of Phase Change Slurries for Thermal Energy Applications
Bibliographic record
Abstract
Phase change materials that leverage the latent heat of solid–liquid transition have many applications in thermal energy transport and storage. When employed as particles within a carrier fluid, the resulting phase change slurries (PCSs) could outperform present-day single-phase working fluids─provided that viscous losses can be minimized. This work investigates the rheological behavior of encapsulated and nonencapsulated phase change slurries (PCSs) for applicability in flowing thermal energy systems. The physical and thermal properties of the PCS candidates, along with their rheological behavior, are investigated below and above their phase transition points at shear rates of 1–300 s –1, temperatures of 20–80 °C, and concentrations of 15–37.5 wt %. The effect of shell robustness and melting on local shear thickening and global shear thinning is discussed, followed by an analysis of the required pumping power. A hysteresis analysis is performed to test the transient response of the PCS under a range of shear rates. We assess the complex viscoelastic behavior by employing oscillatory flow tests and by delineating the flow indices─flow consistency index ( K ) and flow behavior index ( n ). We identify a viscosity limit of 0.1 Pa·s for optimal thermal performance in high-flow applications such as renewable geothermal energy.
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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 | 0.000 | 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".