Innovative flexible thermal storage textile using nanocomposite shape-stabilized phase change materials
Bibliographic record
Abstract
Abstract A novel flexible thermal storage system based on organic phase change materials (PCMs) deposited on a non-woven polyester (PET) substrate is described in this article. Thermally regulating effects were created via encapsulation of polyethylene glycol (PEG) in carbon nanofibers (CNFs) to manufacture a shape-stable phase change material (SSPCM). Improvement in the thermal conductivity (TC) of the system was obtained by incorporating reduced graphite oxide nanoparticles (rGONP) into the CNFs. A new method was applied to load and secure the manufactured SSPCMs on the fibrous substrate so that an acceptable level of flexibility was preserved (change in bending length less than 30%). The sample performance was evaluated by measuring its thermal properties. The physical properties, wash fastness, abrasion resistance, morphology, and PCM leakage of the samples were also assessed. The results point to a good thermal storage ability of the samples with characteristic phase change temperature ranges of 30.1–31.4 °C and 19.2–24.3 °C for melting and freezing, respectively, and a latent heat of 8.9–22.9 J g −1 for meting and 11.2–21.4 J g −1 for freezing. The use of the CNF-rGONP for PEG enhanced the TC of the system by 454%, thus providing a rapid thermal response, and efficiently prevented the leakage of PEG. Finally, the loading and fixation method on the non-woven substrate allowed an acceptable level of durability with less than 4% of weight loss during washing and abrasion tests. This system provides a promising solution for rapid response, flexible thermal storage wearables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".