Unravelling the Effect of Chain and Branch Content on Viscosity of Polyisobutylene-Mineral Oil Blends by Modelling and its Tribological Properties
Bibliographic record
Abstract
The viscosity index is a fundamental property of lubricating oils and greases that significantly affects their lubrication performance under diverse temperature conditions. This study aims to investigate the influence of chain length and branch content on the viscosity of polyisobutylene (PIB)-blend mineral oil. To achieve this objective, mathematical models are employed to predict the specific volume, Vander Waals volume, structural factor, friction factor, molecular weight, and specific viscosity of lubricant blends and their correlation with macromolecular structure. Furthermore, analytical techniques such as Gel Permeation Chromatography (GPC), Nuclear Magnetic Resonance (NMR), and CHNS elemental analyzer are utilized to forecast the appropriate molecular structure of mineral-based oil. The purpose of this research is to comprehend the impact of the macromolecular structure of lubricants on their viscosity, particularly in the case of polyisobutylene (PIB)-blend mineral oil. Overall, the concentration of PIB was found to directly influence the friction (15.3%) and wear (5.6%) performance of the mineral oil explored following ASTM 4172 standard. The mathematical models and analytical techniques employed used in this study can accurately forecast the specific volume, Vander Waals volume, structural factor, friction factor, molecular weight, and specific viscosity of lubricant blends and their relationship with macromolecular structure.
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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".