DIMENSIONAL STABILITY AND TENSILE STRENGTH OF WOOD PLASTIC COMPOSITE FORMED WITH HIGHER PLASTIC CONTENT
Bibliographic record
Abstract
This study investigated the dimensional stability and strength properties of plastic bonded composites produced from wood waste particles and polyethylene using extruder. The composites were produced from wood species such as such as: Triplochiton scleroxylon, Terminalia superba and Gmelina arborea at a mixing proportion of 60:40 (plastic/wood) on a weight by weight basis. Evaluation of properties was carried out in accordance with the American Standard Testing Methods of 570 and 790 to determine the dimensional stability and strength properties of the composites. The results of findings revealed that water absorption and thickness swelling of the wood composites ranged from 10.08% to 15.36% and 4.33% to 5.58% respectively after 24hours and 48hours immersion in water. Tensile strength also ranged between 29.4MPa and 45.6MPa. Composite board made from T. superba wood particles had the lowest significant water absorption (10.08%), thickness swelling (4.33%) and highest significant tensile strength (45.6MPa) compared to composites produced from G. arborea and T. scleroxylon wood particles. It was observed that high density wood species exhibit lower water intake, lower thickness swelling and higher tensile strength, while the contrary is the case for lower density wood species. In conclusion, the three tree species used for the study could be recommended for the production of wood composite like particle board, fibre board, wood cement boards and others.
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 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".