Cellulose and lignin as carbon black replacement in natural rubber
Bibliographic record
Abstract
Abstract Lignocellulosic fillers have gained attention as biofillers due to their low cost, availability, and eco‐friendly nature. Various lignocellulosic fillers from different sources having different chemical compositions have been used in natural rubber (NR) without sufficient comparison. So the objective of this study is to investigate the effect of two well defined industrial fillers (lignin and cellulose) along with black spruce cellulosic pulps obtained from an organosolv process on the properties of NR. To this end, a range (0/100–100/0) of lignin/cellulose (L/C) ratios is prepared. The biobased materials are chemically extracted from black spruce sawdust to partially replace carbon black (CB) in NR composites. The results show that higher L/C ratios provide higher tensile strength and elongation break, while lower ratios produce higher tensile modulus and hardness. These results indicate that a balance between different mechanical properties can be achieved by controlling the L/C ratio. A discussion on the total replacement of CB by lignin or cellulose is also presented to produce a more biobased compound.
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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".