Structural changes of cationic grafted lignin at different drying temperatures
Bibliographic record
Abstract
The reaction of glycidyl-trimethylammonium chloride (GTMAC) with lignin is promising since it generates a cationic lignin derivative with potential applications in various fields, such as wastewater treatment, ion exchange resin, dye, and textile manufacturing. Drying is an important step of polymer fabrication. This work investigates the effect of drying temperatures (-55, 80, 105, and 130ºC) on the properties of kraft lignin (KL) and cationic kraft lignin (CKL). For KL, condensation products were detected after oven-drying. Specifically, after drying at 80 and 105ºC, benzo dioxane structures and diphenylmethane-type structures were observed. Additionally, an increase in molecular weight and glass transition temperature was observed for the samples dried at 105ºC. For CKL, nitrogen-containing groups were degraded in addition to condensation. Additionally, the molecular weight of the CKL samples increased with increasing drying temperature, reaching its peak molecular weight at 105ºC, but it dropped significantly after drying at 130ºC. The CKL samples exhibited lower glass transition temperatures than KL after drying. This work demonstrates that the drying temperature of cationically grafted lignin is an important consideration in conserving the desired properties of the material. • Impact of drying temperature on the properties of cationic grafted lignin was investigated. • High temperature of 130 °C affected the properties significantly. • The Tg and molecular weight of lignin were affected significantly by temperature. • The mechanism of lignin degradation was studied systematically.
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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".