Structural insights of sulfoethylated kraft lignin at different drying temperatures
Bibliographic record
Abstract
Sulfonated lignin has potential applications in various fields, including wastewater treatment, the textile industry, and construction. Although the reaction chemistry of sulfonated lignin has been well studied, the method of drying this material after synthesis has not been evaluated. In this study, sulfoethylated kraft lignin (SEKL) was synthesized as a representative sulfonated lignin to investigate the impact of drying temperature on its structure and properties. For SEKL, freeze-drying at –55 °C resulted in the highest charge density, water-solubility, and more uniform chemical structures. The sulfonic acid groups underwent alkylation reaction after the sample was oven-dried at 55 and 80 °C, which was accompanied by a reduction in solubility and charge density of the sample, as well as an increase in glass transition temperature. Furthermore, the sample after drying at higher temperatures of 105 and 130 °C not only exhibited the alkylation but also underwent hydrolysis of the sulfonic acid groups at the phenolic position of lignin. This change was accompanied by a further reduction in molecular weight, solubility, and charge density, as well as a decrease in the glass transition temperature. It was found that the alkylation and hydrolysis of SEKL occurred to varying degrees, and higher temperatures promoted hydrolysis. Based on the results of this work, drying temperature has a significant effect on the properties of the SEKL sample, implying that it must be taken into account when considering its application in different fields.
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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 | 0.001 |
| 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".