Lignin valorization: lignin nanoparticles as high-value bio-additive for multifunctional nanocomposites
Bibliographic record
Abstract
Although conversion of low value but high-volume lignin by-product to its usable form is one of the determinant factors for building an economically feasible integrated lignocellulose biorefinery, it has been challenged by its structural complexity and inhomogeneity. We and others have shown that uniform lignin nanoparticles can be produced from a wide range of technical lignins, despite the varied lignocellulosic biomass and the pretreatment methods/conditions applied. This value-added nanostructure lignin enriched with multifunctional groups can be a promising versatile material platform for various downstream utilizations especially in the emerging nanocomposite fields. Inspired by the story of successful production and application of nanocellulose biopolymer, two types of uniform lignin nanoparticles (LNPs) were prepared through self-assembling of deep eutectic solvent (DES) and ethanol-organosolv extracted technical lignins derived from a two-stage fractionation pretreatment approach, respectively. Both LPNs exhibited sphere morphology with unique core–shell nanostructure, where the DES–LNPs showed a more uniform particle size distribution. When incorporated into the traditional polymeric matrix such as poly(vinyl alcohol), these LPN products displayed great potential to formulate a transparent nanocomposite film with additional UV-shielding efficacy (reached ~80% at 400 nm with 4 wt% of LNPs) and antioxidant functionalities (reached ~160 μm mol Trolox g−1 with 4 wt% of LNPs). At the same time, the abundant phenolic hydroxyl groups on the shell of LNPs also provided good interfacial adhesion with PVA matrix through the formation of hydrogen bonding network, which further improved the mechanical and thermal performances of the fabricated LNPs/PVA nanocomposite films. Both LNPs are excellent candidates for producing multifunctional polymer nanocomposites using facile technical route. The prepared transparent and flexible LNPs/PVA composite films with high UV-shielding efficacy, antioxidant activity, and biocompatibility are promising in the advanced packaging field, which potentially provides an additional high-value lignin product stream to the lignocellulose biorefinery. This study could open the door for the production and application of novel LNPs in the nascent bioeconomy.
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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".