Capillary Sensor with UV-VIS Reading of Effects of Diesel and Biodiesel Fuel Degradation in Storage
Bibliographic record
Abstract
The diesel fuel stability is related with the fuel composition that evolved to the modern fuels from the historical ones. The stability of modern diesel fuel is mainly due to the reduction of the oxidation processes, the result of the presence of unsaturated components and components with oxygen as organic components and cetane index improvers. These fuel components may form insoluble particles and gum that can contribute to rapid fuel injection system wear and filter plugging. Therefore, the simple characteristic of serious degradation of diesel fuel is the appearance of resins and sediments. The present paper concentrates on the development of simple measurement procedure that can find application in construction of low cost the capillary sensor which enables the examination of the stability of modern diesel fuel including classification of not degraded fuel, fuel on first stage of degradation and serious degraded fuel. As a basic of development the degradation of most widely used cetane improver (2-ethyl hexyl nitrate) and presence of resin are examined in one arrangement. Results of a sensor working on the principle of scattered signal and fluorescence excited in a disposable capillary cell with two, UV and VIS, high power light emitted diodes are presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".