Hydrophobic, Mechanically Robust, and UV-Blocking Paper Enabled by Lignin Reinforcement
Bibliographic record
Abstract
Traditional paper is sensitive to water due to the strong capillary action and abundance of hydrophilic hydroxyl groups in cellulose. Inspired by outstanding properties of lignin, i.e., hydrophobicity, UV-blocking, and thermal stability, lignin-filled hardwood paper (LHP) was produced for various advanced applications. To enhance the lignin retention on the cellulose fibers, we mechanically beat the fibers to different degrees. Results showed that intensive beating made the fibers more fibrous, which significantly increased the lignin retention on the fibers. Benefiting from these changes, more lignin interacted with cellulose fibers, resulting in an increase in the hydrophobicity of lignin-filled hardwood paper (water contact angle (WCA) increased from 42 to 109°). Meanwhile, the water vapor transmission rate (WVTR) of LHP-90 °SR was only half that of the control (786 g/m 2 ·24 h), and its water absorption was as low as 49%. These data further confirmed the excellent hydrophobic properties of LHP-90 °SR, which was attributed to the phenylpropane units and aromatic groups in the lignin molecules. Due to the dense fiber network formed by intensive beating, the interaction between lignin and cellulose was strengthened by hydrogen bonding, thus leading to a remarkable improvement in the tensile strength of lignin-filled hardwood paper from 1 to 41.36 MPa. In addition, lignin filling not only made LHP-90 °SR effective in shielding UV rays but also endowed it with good thermal stability. This research revealed a viable approach to manufacture hydrophobic, thermostable, and UV-blocking paper with high strength for advanced food packaging applications.
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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".