Investigations of Thermal Conductivity for Palm Fronds and Egg Shell Filled Epoxy Composites
Bibliographic record
Abstract
Thermal conductivity has been improved by using epoxy reinforcement techniques extensively.Thus, combining natural materials (egg shell particles and palm fronds) to epoxy is the focus of this work's reinforcement.Different percentages of particles (4, 6, 8 and 10%) were used the effect of adding egg shell (ES) and palm fronds (PF) particles to the epoxy resin has been studied during thermal conductivity tests under natural conditions and immersion in an acid solution (HCl) for a period of (14 days) with normality (0.3 N).Thermal conductivity test results under natural conditions (N.C) showed that epoxy reinforced with palm fronds particles (EP/PF) increased with increasing weight percent (wt%), but thermal conductivity values (K) for egg shells particles (EP/ES) decreased with increasing weight percentage, while immersion in acidic solution (HCl) exceeds the (K) values after immersion more than the value in (N.C).
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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".