Influence of lignin accessibility on chemical and biological decomposition of lignin/polyethylene composite thermoplastics
Bibliographic record
Abstract
Abstract Kraft lignin has been widely investigated for blending with a large variety of polymers to produce thermoplastic composites. The ratio of lignin and polymer affects the accessibility of lignin to small molecules and microorganisms, thus influencing the degradation of lignin/polymer composites. In this present work, the stability and degradation of lignin‐polyethylene composites of different compositions in different environments, including water, acidic solution, alkaline solution, and soils have been investigated. The effects of composite composition (with PE content in the range of 30‐80 wt%) and in turn lignin accessibility on the degradation have been elucidated, with some valuable findings disclosed. The degradation/dissolution of lignin creates new void spaces and water fully or partially fills into these void spaces, depending on the specimen size. Because water does not have any interaction with lignin and PE, most of the lignin degradation behaviour does not affect the dimensional size of lignin/PE composites. However, the dissolution of lignin in alkaline solution leads to significant shrinkage of the lignin/PE composite bar, especially in terms of thickness. The lignin degradation behaviour has different effects on the mechanical strength of lignin/PE composites. The composites with low lignin accessibility degrade minimally in all environments, thus retaining most of the mechanical strength. This study provides insight regarding extending/shortening the life cycle of lignin/polymer composites.
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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".