Influence of UV irradiation on mechanical properties and drop-weight impact performance of polypropylene biocomposites reinforced with short flax and pine fibers
Bibliographic record
Abstract
The design of biocomposite structures for outdoor applications should consider the influence of ultraviolet (UV) irradiation on the mechanical performances to more accurately determine their durability characteristics and prevent significant damage. Ultraviolet radiation causes the discoloration, surface roughness, mass loss, and degradation of the mechanical properties of biocomposites. In this study, the flexural strength and low-velocity impact response of polypropylene reinforced with short flax or pine fibers, which differed with respect to their physical and chemical properties, were investigated. Flax fibers are twice the length of pine fibers, and exhibit higher cellulose contents. Moreover, flax fibers have been demonstrated to increase the flexural strength and impact resistance of biocomposites. However, under UV irradiation, pine fibers containing more lignin dampened the degradation. Under photo-oxidative conditions, lignin is degraded to protect crystalline cellulose by acting as a light-absorbing compound. Non-destructive techniques such as Fourier transform infrared spectroscopy (FTIR), colorimetry, confocal imaging, acoustic emission, and CT scanning were therefore used to evaluate the effect of UV radiation on the chemical properties, color change, surface roughness, bending behavior, and drop-impact damage.
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".