Latent Thermal Energy Storage System for Heat Recovery between 120 and 150 °C: Material Stability and Corrosion
Bibliographic record
Abstract
Thermal energy represents more than half of the energy needs of European industry, but is still misspent in processes as waste heat, mostly between 100 and 200 °C. Waste heat recovery and reuse provide carbon-free heat and reduce production costs. The industrial sector is seeking affordable and rugged solutions that should adapt the heat recovery to heat demand. This study aims to identify suitable latent heat materials to reach that objective: the selected candidates should show good thermal performance that remains stable after aging and, in addition, be at a reasonable price. This paper details the selection process and aging results for two promising phase change materials (PCMs): adipic and sebacic acid. They showed, respectively, melting temperatures around 150 °C and 130 °C, degradation temperatures (mass lost higher than 1%) above 180 °C, and volumetric enthalpy of 95 and 75 kWh·m−3. They are both compatible with the stainless steel 316L while their operating temperature does not exceed 15 °C above the melting temperature, but they do not comply with the industrial recommendation for long-term use in contact with the steel P265GH (corrosion speed > 0.2 mm·year−1).
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".