Characterization of Thevetia Peruviana (Yellow Oleander) Shell Ash Powder as a Possible Filler in Polymer Composites
Bibliographic record
Abstract
In this study, the characterization of Thevetia Peruviana shell powder and Thevetia ash powder incinerated at various temperatures (400, 500, 600, 700, 800 and 900ᵒC) is presented. The Thevetia shells were sourced, sun dried for three days and thereafter grounded into powder. The process of making the ash involves heating the powder to the desired temperature followed by conditioning it at the same temperature for 3 hours and then cooling to a room temperature in the furnace. Elemental compositions of both Thevetia shell powder (TSP) and Thevetia ash powers (TAP) were determined using SEM-EDS analysis. The crystallinity, as well as the phases present, was evaluated with the aid of X-ray diffraction (XRD) and the results revealed that TSP is completely amorphous while TAP showed some level of crystallinity depending on the ashing temperature. Through Fourier Transform Infrared (FTIR), functional groups peculiar to TSP and TAP were elucidated which characterize both the shell powder and the ash samples. Thermal stability of the TSP and TAP was studied using differential scanning calorimetry in the temperature range (25-350ᵒC) and the absence of volatile matters and moisture were observed in the ash samples. Scanning electron microscopy study of the samples showed that TSP image is smooth without porous structure while TAP images are fine, rough and porous, thus making the ash suitable filler materials in polymer matrix composites. Finally, Thevetia powder ashed at 600ᵒC has proven to be the best candidate filler material in the polymer matrix due to its high silica to alumina ratio as well as its characteristic morphology.
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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 | 0.001 | 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".