A green composite hydrogel based on xylan and lignin with adjustable mechanical properties, high swelling, excellent <scp>UV</scp> shielding, and antioxidation properties
Bibliographic record
Abstract
Abstract This study successfully prepared a novel green composite hydrogel based on carboxymethyl xylan and lignin with adjustable mechanical properties, high swelling, excellent UV shielding, and antioxidation performance. The structure and morphology of the hydrogel were characterized by Fourier transform infrared spectra, scanning electron microscopy, thermogravimetric analysis, rheological analysis, and swelling ratio. Results showed that lignin could significantly improve the mechanical properties of composite hydrogels. The compression stress and toughness of the composite hydrogel contained lignin increased by 39% and 60%, respectively, and the compressive deformation reached 90%. In addition, the addition of lignin increased the swelling ratio of the composite hydrogel reached 79.9 g/g. In addition, the composite hydrogel exhibited excellent UV shielding and antioxidation performance. The removal ratio of UV and free radicals is as high as 80% and 90%, respectively. The simple procedure and cost‐effective lignin as raw material for hydrogel with adjustable properties are favorable for medical‐biological 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".