Kraft lignin as wet-strength and wet-stiffness additives for molded pulp materials
Bibliographic record
Abstract
Derived from renewable resources, cellulose based materials are gaining new importance due to their recyclability and biodegradability. Still, one fundamental challenge is their high sensitivity to water. The addition of wet strength agents (WSA) is hence necessary to maintain strength and integrity in humid or wet conditions. In this article, technical lignin was used as WSA in bleached kraft pulp, which was thermopressed to materials with the potential to replace plastics. Cationic starch or a cationic flocculant (PCB 20) was used as a retention aid during the filtration process. The effect of moisture during thermopressing and lignin particle size were also studied. The results showed that elevated moisture during pressing had the biggest impact both on dry and wet strength. Wet strength (tensile test), up to 9 MPa, and wet strength retention, up to 12 %, were obtained when moisture was present during pressing. However, the type of flocculant and the size of the lignin particles also had a limited effect on the strength. Wet strength improvement was most probably due to the plasticization of lignin at high temperatures, which was further aided by water. The cellulose-lignin network was strengthened by the melting of lignin, consolidating the network after cooling. The wet stiffness of the cellulose substrates was also increased from 200 to 938 MPa in the presence of lignin, while the elongation was maintained and no embrittlement was observed. The results in this article might hence pave the way for new developments in molded pulp and cellulose based plastics replacement.
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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) | 0.000 | 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 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".