Viscometric properties of viscosity index improvers in lubricant base oil over a wide temperature range. Part I: Group II base oil
Bibliographic record
Abstract
Abstract Capillary viscometry has been employed to measure the viscosities of dilute polymer solutions over the temperature range ‐10 to 150 °C. A Group II base oil containing 95% saturates was used as solvent for an olefin copolymer (OCP), a hydrogenated diene copolymer (HDP), and a polymethacrylate (PMA). These three polymers represent the three major families of viscosity index (VI) improvers used nowadays in lubricant formulations. Intrinsic viscosities and Huggins' constants were also determined. The thickening effects of the olefin copolymer and the hydrogenated diene copolymer were found to be higher at low temperatures (e.g., 40 °C) than at higher ones (e.g., 100 °C), which phenomenon was attributed to stronger intermolecular hydrodynamic interactions at low temperatures, as indicated by the Huggins constants. For the hydrogenated diene copolymer and the polymethacrylate polymer, the viscosity increased abruptly when the temperature went below 10 °C. This unusual observation was attributed to the crystallisation of a small fraction of the base oil. Based on the intrinsic viscosity data, it was concluded that at temperatures between 10 and 150 °C, the polymer coil dimension remains a constant for the olefin copolymer and the hydrogenated diene copolymer VI improvers, but increases with increasing temperature for the polymethacrylate VI improver.
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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 | 0.001 | 0.001 |
| 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".