Unmodified and esterified <scp>K</scp>raft lignin‐filled polyethylene composites: Compatibilization by free‐radical grafting
Bibliographic record
Abstract
ABSTRACT In this study, the effectiveness of free‐radical grafting as a compatibilization method applied to composites containing Kraft lignin (KL) and esterified lignin was comparatively investigated. Maleated lignin (ML) was first obtained via esterification of KL with maleic anhydride. KL and ML were respectively incorporated into high density polyethylene (HDPE) up to 60% wt and dicumyl peroxide was used as a free‐radical generator. The influence of lignin esterification and free‐radical grafting on the morphological, mechanical, and thermal properties of lignin‐based composites was studied. The incorporation of lignins into HDPE resulted in poor mechanical strength because of low compatibility. Morphological and mechanical evidences indicate improved compatibility between lignins and HDPE following free‐radical grafting. The free‐radical scavenging properties of KL allowed better compatibilization of KL‐based composites compared with ML‐based composites. In addition, thermal analysis results showed that free‐radical grafting increases the thermal stability of ML‐based composites. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41484.
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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".