Characterization of Trimethylolpropane‐Based Biolubricant
Bibliographic record
Abstract
Abstract The oxidative stability index (OSI) of fatty acid methyl esters (FAME) and trimethylolpropane (TMP) esters or TMPE produced from five vegetable oils (Brassica rapa L., Linum usitatissimum L., Zea mays L., Brassica napus L., Camelina sativa L.) are compared. The highest stability is observed in vegetable oils while the processed products are less stable. The major causes in loss of OSI are attributed to excess FAME in the crude product and the loss of natural antioxidants due to refinement with silica and celite. The low‐temperature flow properties of TMPE produced from four different vegetable oils (B. juncea L., L. usitatissimum L., B. rapa L., and C. sativa L.) are investigated by proton nuclear magnetic resonance (1H‐NMR). The T2 relaxations of different TMPE are measured to observe how the mobility of oil changed as temperature decreased. Increased oil mobility (represented by T2) is correlated with rising temperature. The Gaussian widths of the singlet in 1H‐NMR spectra of each oil demonstrated increased molecular mobility as temperature increased. Extrapolation of the relation of T2 signals of these four oils indicates that T2 approached zero between 232 K and 239 K, suggesting the molecular motion leading to a T2 relaxation has largely ceased. Practical Applications: The OSI is determined for four vegetable oils as well as the product FAME and TMPE. The vegetable oils are more stable than their products. The loss of natural antioxidants during purification of FAME and TMPE contributes to the lower OSI compared to vegetable oil. The low‐temperature flow behavior of TMP‐based biolubricants is determined between 238 K and 298 K using T2 relaxation. As temperature decreases, a singlet resonance in 1H‐NMR spectra attributed to TMP protons broadens until it disappears. The results suggest that the log of the spin‐spin relaxation time is linearly correlated with rising temperature and oil mobility.
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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".