Enhancing In Situ Burning With Ferrocene for Improved Combustion and Reduced Smoke Production
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Bibliographic record
Abstract
ABSTRACT In situ burning (ISB) is an efficient response strategy for oil spills; however, incomplete combustion and excessive smoke production hinder its wider application. In this study, the effectiveness of using ferrocene as additives to improve the thermal behaviors and kinetics of combustion of different crude oils (Hibernia, Hebron, Dilbit and Bitumen) and commercial Diesel was investigated using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) techniques under atmospheric air condition. The TGA and DSC results revealed that the addition of 1.0 wt% ferrocene to crude oils and Diesel lowered the combustion oxidation reaction temperature up to 80°C, indicating reduced resistance and thermodynamic demand during ISB experiments. Iso‐conversional kinetic modeling using Ozawa–Flynn–Wall (OFW) and Kissinger–Akahira–Sunose (KAS) showed a reduction in apparent activation energy ( E a ) up to 35–50 kJ mol − ¹ in Hibernia and Hebron, 87–182 kJ mol⁻¹ in Bitumen, and 12 kJ mol − ¹ in Diesel, confirming enhanced ignition and reaction rates, whereas Dilbit exhibited a slight increase (~up to 2.6 kJ mol − ¹). To better understand oil oxidation behavior and mechanisms during ISB, TG‐FTIR (Fourier transform infrared spectroscopy) system was employed to analyze the evolved gases at various temperature stages. It was revealed that ferrocene facilitated oxygen addition, bond scission and decarboxylation reactions, resulting into enhanced breakdown of complex, high‐boiling‐point oxygenated hydrocarbons during ISB. Hence, ferrocene hindered the aggregation of molecular species into larger compounds, resulting in less smoke production in ISB and these findings will inform future ISB experiments in open water bodies.
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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 | 0.001 | 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) | 0.000 | 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