Experimental Thermal Conductivity Measurements for the Hydrofluoroolefin R1225ye(Z)
Bibliographic record
Abstract
Abstract In the pursuit of a fourth generation of refrigerants characterized by zero Ozone Depletion Potential and remarkably low Global Warming Potential (GWP), as mandated by EU Regulation No 517/2014 and the Kigali Amendment to the Montreal Protocol, natural refrigerants and hydrofluoroolefins (HFOs) have emerged as the most promising long-term alternatives. Notably, the hydrofluoroolefin cis-1,2,3,3,3-pentafluoroprop-1-ene R1225ye(Z) and its isomers have been considered as environmentally friendly options to replace the widely used R410A in refrigeration applications, both in pure form and blends, due to their similar characteristic pressures and temperatures. However, despite its GWP being lower than 3, studies on the toxicological effects of R1225ye(Z) have prevented its applications in industrial contexts, discouraging the study of its thermophysical properties. To date, the available literature offers only a limited amount of experimental data on the thermophysical properties of R1225ye(Z), with none specifically addressing its thermal conductivity. Thus, this study addresses this gap by presenting a comprehensive dataset of 68 experimental thermal conductivity measurements, performed employing a double transient hot-wire apparatus along eleven isotherms spanning temperatures from 243.15 to 343.15 K, encompassing pressures ranging from close to vapor pressure up to 8 MPa. A simplified correlation for estimating the thermal conductivity at saturation state was developed using the extrapolation method. Then, the experimental thermal conductivity data were compared with a generalized model for liquid thermal conductivity in HFOs, demonstrating good agreement with calculated values (AAD 2.3%), in line with the declared model accuracy.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".