Olive fiber reinforced epoxy composites: Dimensional Stability, and mechanical properties
Bibliographic record
Abstract
Abstract The processing of olive (Olea europaea L.) oil results in large quantities of solid waste consisting primarily of tree pruning remainders from olive trees growing. This has led to the idea of utilizing the leftovers into a value‐added product; natural composite materials are utilized as alternatives to environmentally damaging synthetic materials. This study deals with the evaluation of the filling properties of the residue; olive tree small branch (OTS), olive tree big brunch (OTB) and olive tree leaves powder, for epoxy matrix biocomposite. Olive powder reinforced epoxy composite was processed at 40% filler loading. In this paper, the various forms of impacts of filler within epoxy on the physical and mechanical of epoxy composites were scrutinized by tensile, flexural, impact, thickness swelling, and water absorption tests. From the observation, it was discovered that the tensile and flexural strength of epoxy composite reinforced with OTS and OTB increased by about 27% and 47%, respectively. The impact strength values of OTS and OTB epoxy composites were 8.61, 7.88, and 5.97 J/m, respectively, while the virgin epoxy increased up to 16 J/m. The microstructure of the composites is also analyzed using scanning electron microscopy to analyze interfacial bonding.
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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".