Organic Phase Change Materials for Thermal Energy Storage: Influence of Molecular Structure on Properties
Bibliographic record
Abstract
Materials that change phase (e.g., via melting) can store thermal energy with energy densities comparable to batteries. Phase change materials will play an increasing role in reduction of greenhouse gas emissions, by scavenging thermal energy for later use. Therefore, it is useful to have summaries of phase change properties over a wide range of materials. In the present work, we review the relationship between molecular structure and trends in relevant phase change properties (melting temperature, and gravimetric enthalpy of fusion) for about 200 organic compounds from several chemical families, namely alkanes (paraffins), fatty acids, fatty alcohols, esters, diamines, dinitriles, diols, dioic acids, and diamides. We also review availability and cost, chemical compatibility, and thermal and chemical stabilities, to provide practical information for PCM selection. Compounds with even chain alkyl lengths generally give higher melting temperatures, store more thermal energy per unit mass due to more efficient packing, and are of lower cost than the comparable compounds with odd alkyl chains.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".