Review on Thermal Properties with Influence Factors of Solid–Liquid Organic Phase-Change Micro/Nanocapsules
Bibliographic record
Abstract
Solid–liquid organic phase-change micro/nanocapsules are potential candidates for energy storage. Recently, significant progress has been made regarding phase-change micro/nanocapsules in terms of their synthesis, properties, and applications. Extensive research has been conducted to enhance their thermal properties, such as thermal storage capacity, thermal conductivity, and thermal reliability. However, factors that influence the thermal properties of micro/nanocapsules have received little attention. This study presents a comprehensive review of phase-change micro/nanocapsules focusing on their thermal properties and their influencing factors. In addition, the thermal properties of the major solid–liquid organic pure phase-change materials are summarized. Furthermore, common micro/nanoencapsulation methods and their influence on the thermal properties were analyzed. Finally, the potential applications of these phase-change micro/nanocapsules were also investigated. This study was devoted to enhancing the thermal properties of micro/nanocapsules, which play a crucial role in their practical applications.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".