Effect of irradiation on the composition and thermal properties of softwood kraft lignin and styrene grafted lignin
Bibliographic record
Abstract
ABSTRACT Lignin is an abundant, underutilized natural resource that has potential to be used as a biomaterial but is currently hampered in its use by not being uniform in structure and composition and is thermally unstable due to phenolic group. To address these issues and modify its thermal properties, softwood kraft lignin was modified using γ‐irradiation at low doses with and without styrene present and characterized. Irradiation of kraft lignin alone with γ‐radiation shows an initial decrease in molecular weight due to chain scission up to about 10 kGy followed by an increase in molecular weight due to crosslinking. NMR results indicate a decrease of about 15% in the OH content of the lignin with 30 kGy irradiation. Thermal properties such as Tg, free volume and ΔCp follow accordingly. Irradiation at very low dosages was determined to facilitate the grafting of styrene monomer to lignin, decreasing the OH content by 23%. This effect increased the hydrophobicity of the material, depressed the value of Tg, increased the ΔCp, increased the mobility in the liquid state, and made the material more thermally stable relative to the lignin alone, thus improving its processability at high temperatures. Both the irradiation of lignin alone and the grafting of styrene to lignin increased the yield of mass during pyrolysis and the activation energy for mass loss relative to untreated lignin alone. This work has demonstrated that the application of low dosages of γ‐irradiation is a promising method to attach functional molecules onto lignin for use in various applications. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014, 131, 39743.
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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) | 0.002 | 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".