Using Mg(OH)2 in peroxide bleaching of wheat straw soda-AQ pulp
Bibliographic record
Abstract
The peroxide bleaching of high yield pulps from wood with Mg(OH)2 has been developing recently in the pulp and paper industry. However, there is still a lack of data on the application of Mg(OH)2 in peroxide bleaching of non-wood fibres. In this work, our purpose was to study the effect of Mg(OH)2 on peroxide bleaching of wheat straw soda-AQ pulp. The results showed that Mg(OH)2 significantly improved peroxide bleaching efficiency (expressed as the ratio between the brightness gain and the H2O2 consumption) and selectivity (expressed as the ratio between the brightness gain and the viscosity losses) of wheat straw soda-AQ pulp. The brightness, viscosity, and yield of bleached pulp can be significantly enhanced by increasing the replacement ratio of Mg(OH)2. However, at 100% replacement of NaOH with Mg(OH)2, the brightness of bleached pulp was much lower than that of the bleached pulp with NaOH as the sole alkaline source. When 24 to 73% of the NaOH was replaced with Mg(OH)2, the COD of the bleaching filtrate was 11 to 38% lower than that of the NaOH as the sole alkaline source. The lower solubility and alkalinity of Mg(OH)2, as well as the reduction of Cu ion content in bleached pulp were proposed as accounting for the favorable effect of Mg(OH)2 on peroxide bleaching of wheat straw soda-AQ pulp.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".