ZnO Treatment on Mechanical Behavior of Polyethylene/Yellow Birch Fiber Composites When Exposed to Fungal Wood Rot
Bibliographic record
Abstract
Wood plastic composite (WPC) usage and demand have increased because of its interesting chemical and mechanical properties compared to other plastic materials. However, there is a possibility of structural and mechanical changes to the material when exposed to the external environment; most research on wood plastic is performed on the material with elevated fiber content (40–70%). Therefore, more research needs to be performed regarding these issues, especially when the fiber content of the WPC is low. In this study, composite materials composed of high-density polyethylene (HDPE) reinforced with yellow birch fibers (20 and 30%) were made by injection molding. The fibers were treated with dissolved zinc oxide (ZnO) powder in sodium oxide (NaOH) solution, and the fabricated material was exposed to fungal rot. ZnO treatment in this case is different from most studies because ZnO nanoparticles are usually employed. The main reason was to obtain better fixation of ZnO on the fibers. The mechanical properties of the composites were assessed by the tensile and Izod impact tests. The impact energies of the samples fabricated with ZnO-treated fibers and exposed to Gloephyllum trabeum and Trametes versicolor decreased, when compared to samples fabricated with ZnO-nontreated fibers. The mechanical properties of the samples composed of ZnO-treated fibers and exposed to rot decreased, which were reported by a decreased Young’s modulus and impact energies. The usage of ZnO treatment prevented mycelium proliferation, which was nonexistent on the samples. It has been noted that the decrease in mechanical properties of the treated samples was because of the action of NaOH used to dissolve the ZnO powder.
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".