Development of a Free Lime Monitoring System for the Kraft Recovery Process using Zeta Potential
Bibliographic record
Abstract
The presence of Ca(OH)2 (or free lime) in lime mud can cause many problems in the recovery process of kraft pulp mills. Conventional free lime analyses require extensive laboratory work and give inconsistent results. A systematic study was performed to determine if zeta potential, a quickly measurable dispersion characteristic, can be used to indicate the presence of free lime in the recovery process. Measurements were made on synthetic wet lime mud to simulate samples collected after the white liquor clarifier in pulp mills. The results show that zeta potential increases from negative to positive when the free lime content in the lime mud exceeds a critical threshold. This change from negative to positive zeta potential of the lime mud slurry can be used as a basis for developing an on-line monitoring system that effectively detects free lime in the lime mud in order to avoid problems associated with overliming in the recovery process.
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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".