The Effect of Yellowing Inhibitor Total Charge on The Rheology of Paper Coating
Bibliographic record
Abstract
Abstract New compounds, called inhibitors, provide anti-yellowing effect for mechanical pulps and papers, when added to the coating formulation. The rheology of coating mixtures, which contain clay, ground calcium carbonate, starch, latex, inhibitors and other minor additives, affects to a certain extent the final quality of the coated paper. The purpose of this work is to investigate the effect of the total weight charge of inhibitors, when present between coating color ingredients, on the thixotropy and visco-elasticity of the mixture and other rheological properties. We also study the degree of interaction between inhibitor and coating ingredients using Transmission Electron Microscope (TEM) and water retention measurements. For the industrially preferred inhibitor system of low RS/UVA ratio and high total charge the coating formulation will have a significant increase in the general value of viscosity and a clear and profound shear-thinning behavior. Under the desired conditions of higher total charge the coating formulation acquires significant thixotropic behavior. A higher level of energy is required to coat such formulation. The elastic modulus increases with frequency. This rise in the elastic modulus reveals the increasing interaction between particles in the coating formulation. The total charge does not affect the resistance of a coating color to the applied stress. The coating color with low total charge has the strongest water holding capability decreasing with increasing total charge.
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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) | 0.000 | 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) | 0.002 | 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".