Morphological and Wettability Properties of Thin Coating Films Produced from Technical Lignins
Bibliographic record
Abstract
Abstract Technical lignins are widely available as side streams from pulping and biorefining processes. The aromatic structure of such lignins could be exploited in coating formulations to provide antioxidant or UV-blocking functionalities to packaging films. In this study, six technical lignins sourced from different plant species by given isolation/modification methods were compared for their composition, molar mass, and functional groups. The lignins were then used to prepare thin spin-coated films from aqueous ammonia media. All the lignins formed ultrathin (<12 nm), smooth (roughness < 2 nm), and continuous films that fully covered the solid support. Most of the films contained nanometer-sized particles, while those from water-insoluble lignins also presented larger particulate features, which likely originated from macromolecular association during solvent evaporation. These latter films had water contact angles (WCAs) between 40 and 60°, corresponding to a surface energy of 42–48 mJ/m2 (determined by Zisman plots). For comparison, the water wettability measured on lignin pellets obtained by mechanical compression tracked closely with the WCA obtained from the respective thin films. Considering the widely diverse chemical, molecular, and structural properties of the tested lignins, comprehensively documented here by using a battery of techniques, the solubility in water was found to be the most important and generic parameter to characterize the thin films. This points to the possibility of developing lignin coatings with predictable wetting behavior.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".