Thermal properties and performance of glycerol-water-NaCl phase change material for cold chain applications
Bibliographic record
Abstract
This study investigates the thermal properties of glycerol-water mixtures and their potential as P hase C hange M aterials ( PCM s) for C old T hermal E nergy S torage ( CTES ) in cold chain applications. The study characterizes key thermal properties, including P hase C hange T emperature ( PCT ), latent heat, density, thermal conductivity, and specific heat. Results indicated that increasing glycerol concentration decreased the PCT of the mixture, reaching −7.76 °C to −21.82 °C, at glycerol concentrations ranging between 25 wt% to 45 wt%, respectively. However, this decrease in PCT is accompanied by a reduction in latent heat, 147.5 kJ·kg −1 to 73.6 kJ·kg −1 for the respective concentrations. To enhance the PCM properties and achieve optimal thermal performance, NaCl was added as an additive to the glycerol-water mixture. The R esponse S urface M ethodology ( RSM ) was employed to optimize the concentrations of PCM components, aiming to achieve a desired PCT of −20 °C and maximize latent heat capacity. The developed model demonstrated high predictability, with an R 2 of 99.20 %, and good statistical significance, as indicated by an overall model F-value of 98.68 and a P-value of 0.0003. Based on this optimization, three mixtures were selected for further characterization, exhibiting suitable PCT values of around −20 °C to −18 °C and latent heat capacities ranging from 97 kJ·kg −1 ( PCM-M1 ) to 280 kJ·kg −1 ( PCM-M3 ). A one-dimensional model was developed to assess the impact of optimized PCM-M3 on the temperature stability of frozen food products. Incorporating the PCM layers significantly improved the thermal control of the perishable product. During standard freezer operation, the product temperature was maintained at −20 °C ± 0.065 °C compared to the reference case (without PCM) at −20 ± 0.81 °C. During defrost cycles, and using PCM-M3 , the maximum product temperature reached −19.42 °C, compared to −16.98 °C without PCM.
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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".