Development of high bio‐content polypropylene composites with different industrial lignins
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sustainability, eco‐efficiency, pollution prevention, industrial ecology, and green chemistry are considering platform‐based approaches to the development of the next generation of products and processes. Recently, renewable alternatives to traditional petroleum‐derived plastics have motivated recent interest in bio‐based composite materials which can contribute to the reduction of the environmental footprint. Lignin is a complex and amorphous biopolymer with a high density of functional groups and high modulus, which makes it potentially promising for material applications. In this sense, lignin can potentially be employed to improve the performance of materials and an economical alternative to convert lignin into high value‐added materials. Two different types of Kraft lignin were incorporated into polypropylene to fabricate composites with high bio‐content. In this study, polypropylene, Kraft lignin, and coupling agent were subjected to reactive extrusion. The composites prepared by melt processing were compared in terms of morphological, mechanical, and thermal characterizations. The results revealed that the incorporation of lignin into polypropylene matrix resulted in composites with properties suitable for various industrial sectors, especially those in which mechanical and thermal properties are crucial, such as the replacement of engineering plastics and polypropylene mineral filled. As a result, this work provides an effective way of using lignin as a low‐cost bio‐renewable resource in the plastics industry.
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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) | 0.000 | 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) | 0.000 | 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 it