Decreasing the peroxide decomposition in the magnesia slurry
Bibliographic record
Abstract
Abstract The peroxide bleaching process for mechanical pulps using weak alkali sources such as magnesium hydroxide (Mg(OH)2), received much attention recently. The magnesia slurry (containing 61.2% Mg(OH)2) can be used for this purpose. In this paper, we studied the manganese‐induced peroxide decomposition in commercial magnesium hydroxide slurry (magnesia). The results showed that peroxide decomposition occurs under the conditions of magnesia based bleaching process. This is due to impurities, particularly manganese in the magnesia slurry. Similar to the conventional sodium hydroxide based process, sodium silicate can effectively decrease the manganese‐induced peroxide decomposition. However, the amount of silicate required is significantly less. It was found that diethylenetriaminepentaacetic acid (DTPA) or its sodium salt, can also be an effective stabiliser in the system. The chemistry of the manganese‐induced peroxide decomposition was discussed.
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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".