Characterization of phase-changing materials as stabilized thermal energy storage in impregnated biomaterial
Bibliographic record
Abstract
In recent years, impregnation of biomaterial (wood veneers) with eutectic phase change materials (PCM) has been investigated to increase the thermal capacity of bio-based materials, which significantly affects the thermal capacity, especially in building applications requiring low heat. In this study, four eutectic phase change materials were prepared using three different fatty acids and impregnated on two wood veneers (oak and ash). The structural characterization of the prepared eutectic mixtures was examined using FT-IR, while the morphological properties of the wood veneers were examined by scanning electron microscopy (SEM). The thermal performance was analyzed via differential scanning calorimetry (DSC) and their thermo-mechanical properties by dynamic mechanical analysis (DMA). Additionally, the thermal conductivity ( k values) was determined. From the results obtained, it was possible to prepare eutectic mixtures with melting temperatures around 30°C with heat capacities up to 225.5 J/g. It was also generally determined that eutectic PCM, prepared from mixtures of lauric acid and palmitic acid, have lower thermal conductivity but show higher storage and loss modulus for the wood coatings leading to a balance between mechanical and thermal properties.
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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 | 0.000 |
| 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".