Tribological and thermo-physical properties of jatropha oil containing TiO<sub>2</sub> nanoparticles
Bibliographic record
Abstract
In this paper, an attempt was made to evaluate the tribological aspects of Al 6082 under lubricated conditions. The bio-lubricant jatropha oil was used, and its performance was compared with SAE20W40 engine oil. For enhancing the lubricating properties of jatropha oil, TiO2 nanoparticles were used. Experiments were conducted with pure jatropha oil with different weight percentages of TiO2 nanoparticles, such as 0%, 0.1%, 0.3%, and 0.5%. The coefficient of friction and specific wear rate of the Al specimens were determined using a pin-on-disc tribo-meter as per ASTM G99 standards, at a constant speed of 1 m/s and different loads, such as 20, 40, and 60 N. The experimental results indicated that the addition of TiO2 to jatropha oil reduced the friction and enhanced anti-wear properties, compared with SAE20W40 engine oil. The lubricant viscosity and thermal conductivity were measured using a Redwood viscometer and a transient hot wire method. Surface analysis was performed using a scanning electron microscopy to study the surface morphology of the worn-out pin material. Surface examination revealed that TiO2 nanoparticles lead to a smoother worn surfaces than commercial engine oil SAE20W40.
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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 | 0.000 |
| 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) | 0.001 | 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".