Heteroatomic Jet Fuel Components: Lichen Substances as Fuel Component and Potential Additives
Why this work is in the frame
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Bibliographic record
Abstract
This article presents chemical analysis of jet fuel (Jet A-1) heteroatomic fuel components with identification of an antioxidant lichen substance, gyrophoric acid in methanol extracted fuel samples. Thermal stressing of jet fuel produces soluble macromolecular oxidatively reactive species (SMORS) and heteroatomic deposits. SMORS are deposit precursors and elementary heteroatomic units containing unsaturated and aromatic hydrocarbons. Fuel additives such as antioxidants can inhibit SMORS and deposit formation within limited heating residence time and temperature range. Jet A-1 was thermally stressed in the autoxidation regime (150 to 300 0C) followed by spectroscopic analysis. Thermally stressed jet fuel static tests electrospray ionization mass spectra (ESI-MS) show higher molecular weight compounds in the mass range 300-1000 Da compared with unstressed fuel samples supporting deposition. Jet A-1 samples were analyzed by electrospray ion source mass spectrometry (ESI-MS), Fourier transform infrared (FTIR) and 13C nuclear magnetic resonance (NMR) spectroscopy. FTIR bands for oxygen containing species reveal the presence of alcohol, phenol and ether groups. 13C nuclear magnetic resonance (NMR) standard and distorsionless enhancement polarization transfer (DEPT 135) spectra recorded heteroatomic alkoxy species in both unstressed and thermally stressed fuel samples. Natural products polyphenols and lichen derived oxygenated compounds are excellent antioxidants. A new perspective of using lichen substances as fuel additives emerged in this study. Exploring further, natural products extraction methods optimization remains a key challenge and advantages of polyphenolic lichen acids as potential fuel and chemical additives are discussed.
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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 | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it