Oxidation of Kraft Lignin with Hydrogen Peroxide and its Application as a Dispersant for Kaolin Suspensions
Bibliographic record
Abstract
Lignin is an underutilized byproduct of pulping and cellulosic ethanol production plants. However, if utilized efficiently, it can facilitate the development of sustainable processes. In this work, oxidized kraft lignin (OKL) was prepared via treating kraft lignin (KL) with hydrogen peroxide, an environmentally friendly and industrially attractive oxidizing agent, under alkaline conditions. The oxidized kraft lignin with a carboxylate group content of 1.53 mequiv/g was obtained under the optimal oxidation conditions of 80 °C, 2 h treatment, at a 0.77 molar ratio of NaOH/H 2 O 2, and 2.85 molar ratio of H 2 O 2 /lignin, which was then employed as an anionic dispersant for kaolin suspensions. The zeta potential, particle size, and specific surface area as well as the relative turbidity and flocculation index of the kaolin suspension were affected by the pH of the suspension. By increasing the dosage of OKL to 40 mg/L, the relative turbidity of the suspension was increased to 1.18 at pH 5 and the kaolin concentration of 4 g/L, which made its performance superior to that of commercially produced lignosulfonate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".