Changes of Lignin Molecular Structures in a Modification of Kraft Lignin Using Acid Catalyst
Bibliographic record
Abstract
The purpose of this study is to modify lignin for better blending with general purpose synthetic polymers. The possible advantages by using this modification would be cost reduction, better physical properties, and biodegradability. In this study, butyrolactone-modified lignin (BLL) and tetrahydrofuran-modified lignin (THFL) were used for aliphatic chain modification of lignin using an acid-catalyzed esterification method in order to mimic the relation of lignin-carbohydrate-complex (LCC) and cellulose. The results of several analyses indicated that lignin was well modified. It was confirmed that the lignin was modified as expected and the reaction sites of the modification, as well as the reaction behaviors, were varied by the reagent types. The result of X-ray diffraction analysis (XRD) analysis indicated that modified lignin/polymer blends increased the crystallinity due to their good compatibility. It can be confirmed that the type of alkyl chain and the miscibility gap between the alkyl chain-matrix affected the mechanical properties enormously in the fungi-degradable environment. From this study, a new method of lignin modification is proposed, and it is found that modified lignin retains the property of the substituted aliphatic chain well. This method could be a proper lignin modification method.
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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".