Production of Flocculant from Thermomechanical Pulping Lignin via Nitric Acid Treatment
Bibliographic record
Abstract
There is a growing need to utilize lignin (i.e., wasted material) from the pulping industry in the production of value-added products and to develop cost-effective and environmentally friendly processes for removing dyes from wastewater effluents. In this context, lignin can be modified to gain anionic charges, which can successfully remove cationic dyes from wastewater. In this study, lignin was extracted from thermomechanical pulp (softwood) via periodate treatment, and then the extracted lignin was oxidized using 30 wt % nitric acid concentration at 80 °C for 1.5 h, which resulted in oxidized lignin with the charge density and solubility of 3.02 mequiv/g and 97% (at a 1 wt % lignin concentration), respectively. The oxidized lignin was used for removing ethyl violet and basic blue cationic dyes from simulated wastewater effluents. It was observed that the dye removals were in the ranges of 70–80 wt % for ethyl violet and of 80–95 wt % for basic blue, while the COD removals were in the ranges of 60–70% for ethyl violet and 70–85% for basic blue when the concentrations of dyes varied between 50 and 400 mg/L. The dye removal was pH dependent, and the removal of basic blue decreased from 84 wt % (in the absence of salt) to 77% in the presence of 3 g/L NaCl, whereas salt had a marginal effect on the removal of ethyl violet from the solution.
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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".