Bibliographic record
Abstract
The stability of hydrogen peroxide (H2O2) is a critical factor for the brightening of mechanical pulps. Inorganic ions, including Fe, Mn and Cu catalytically decompose H2O2. These troublesome metals promote the rapid transformation of H2O2 to nonselective hydroxyl radicals that degrade the cellulose fibres and decrease yields. The interaction of aqueous metal•complexes with magnesium metal (Mg°) or bimetallic mixtures of magnesium with either palladium (Pd°/Mg°) or silver (Ag°/Mg°) were optimized to remove metals (Mn, Cu and Fe) from solution with concomitant release of the complexing reagent. The analyte metals were removed by both cementation on the surfaces of the excess Mg° and by precipitation as hydroxides. Overall, the reactions were rapid (3 or 10 min) and very efficient. The accelerators (Ag or Pd) were deposited on the surfaces of the Mg°. In a separate study, the excess of Mg° could be reused to mediate more metals removal without apparent loss of reactivity. Among the other iminodiacetate analogs (CDTA, MEDTA, EGTA, HEDTA, DPTA and MTBE), the EGTA and HEDTA proved to be possible substitutes for both efficient metal removal of Mn, Cu and Fe from solution and efficient release of chelating reagent. The measurement of particle size, performed by laser granulometry, demonstrated that smaller particles of precipitate were generated from metal-EDTA complexes by reaction with NaOH than by reaction with Pd°/Mg° bimetallic mixture. If the suspensions of particles were analyzed in the absence of ultrasound, the particles became aggregated into large flocs (up to 150 mum3 ). The reactivity of the bimetallic mixtures was exploited to remove Cu, Mn, Fe, Zn and Al that had been initially chelated with EDTA or DTPA from a thermomechanical pulp (TMP). After 15 min, the metals had been removed efficiently with the bimetallic mixtures. The EDTA released from the TMP filtrate could be recycled efficiently for a total of three cycles. On the other hand, the DTPA was not released as efficiently. Measurements of turbidity and chemical oxygen demand (COD) indicated no appreciable difference between the pulp samples with either chelating reagent. Residual H2O2 and ISO brightness measurements indicated no apparent differences among pulps that had been treated with fresh or recycled EDT A or DTP A.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".