Synthesis and Experimental Thermal Adsorption Characteristics of Epoxy Hybrid Composite for Energy Storage Applications
Bibliographic record
Abstract
Polymer-based matrix hybrid composites meet their demand in various engineering applications and food industries due to their excellent mechanical, thermal, corrosion, and biodegradable performance. The polymer-based hybrid composites have been a better choice for high thermal insulation at low cost. This experiment attempted to find the thermal adsorption characteristics, heat deflection temperature, linear thermal expansion, and thermal conductivity of epoxy hybrid composites, which contained four different layers of Kevlar and basalt fiber fabricated via a low-cost conventional hand mold layup technique. This experiment revealed that the effect of basalt/Kevlar fiber on epoxy increased thermal performance. The results noted that the hybrid composite consists of less Kevlar fiber with the maximum basalt fiber of sample 4, showed excellent thermal adsorption effect on weight loss limited at 70.98%, and a better heat deflection temperature and[Formula: see text]per °C linear thermal expansion were obtained. Sample 3 exhibited a maximum thermal conductivity of 0.251 W/mK. However, the thermal adsorption of hybrid composite has been limited by more basalt fiber, leading to a 1 wt%/°C decomposition rate.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".