Use of Recycled Additive Materials to Promote Efficient Use of Resources While Acting as an Effective Toughness Modifier of Wood–Polymer Composites
Bibliographic record
Abstract
Wood–polymer composites (WPCs) with polypropylene (PP) matrix suffer from low toughness, and fossil-based impact modifiers are used to improve their performance. Material substitution of virgin fossil-based materials and material recycling are key aspects of sustainable development and therefore recycled denim fabric, and elastomer were evaluated to replace the virgin elastomer modifier commonly used in commercial WPCs. Microtomography images showed that the extrusion process fibrillated the denim fabric into long, thin fibers that were well dispersed within the WPC, while the recycled elastomer was found close to the wood fibers, acting as a soft interphase between the wood fibers and PP. The fracture toughness (KIC) of the WPC with recycled denim fabric matched the commercial WPC which was 1.4 MPa m1/2 and improved the composite tensile strength by 18% and E-modulus by 54%. Recycled elastomer resulted in slightly lower KIC, 1.1 MPa m1/2, as well as strength and modulus while increasing elongation and contributing to toughness. The results of this study showed that recycled materials can potentially be used to replace virgin fossil-based elastomeric modifiers in commercial WPCs, thereby reducing the CO2 footprint by 23% and contributing to more efficient use of resources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".