Utilizing macroscopic rheometry to investigate triglyceride self-assembly
Bibliographic record
Abstract
The rheological behavior of a canola oil-based bio-lubricant was correlated with its surface activities using a rotary rheometer. The experiments on the gap size, substrate, and surface conditions led to a consistent and conceivable assumption that the self-assembled monolayer was extended to a degree that was sufficient to make a significant change in the bulk properties. In parallel, the thermal behavior was also connected to the surface activities. Differential scanning calorimetry was used to measure what is thought to be the monolayer melting point without using a graphite substrate. Crystallization points were measured at relatively high temperatures. Tribological tests were conducted and explained based on the rheological and thermal findings. A scenario describing both the boundary and bulk regimes was hypothesized. Rheometry and thermal analysis techniques are promising because of the variety of variables that could be controlled, such as temperature, shear, time, gap and substrate. To the best of our knowledge, this is the first study using macroscopic rheology to study the surfactant activities of vegetable oil. The influence of substrate and gap size on rheological behavior could change the current standards for using rotary rheometers.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".