On the sudden reversal of soot formation by oxygen addition in DME flames
Bibliographic record
Abstract
Dimethyl ether (DME) is a non-toxic and renewable fuel known for its soot emissions reduction tendencies. In laminar co-flow DME diffusion flames, adding oxygen to the fuel stream increases the sooting tendency until a critical point is reached, at which point the trend suddenly reverses. This work unravels the mechanisms behind this reversal process, and characterizes their contribution to controlling soot production. A series of experimental measurements using diffuse-light line-of-sight attenuation and two-colour pyrometry were performed to measure soot volume fraction and soot temperature considering a fixed mass flow rate of DME and variable addition of oxygen. Soot volume fraction increases from 0.095 ppm in the pure DME flame to 0.32 ppm when the added oxygen concentration reaches 33%. When the oxygen concentration is slightly increased to 35%, soot volume fraction is reduced by 60%. To explain the reasons behind the reversal, a series of numerical simulations were performed, which successfully demonstrated the same trend. Results show that the chemical effects of adding oxygen to the fuel stream are exceedingly more important than the thermal and dilution effects. It was found that the reversal occurred when nearly all DME disassociated before exiting the fuel tube, indicating a sudden transition from a partially premixed DME flame, to one which primarily burns C1 fuel fragments. An analysis of soot formation and oxidation rates showed that near the reversal, soot inception is the least affected process; furthermore, soot precursor availability is not significantly affected in magnitude, rather they appear further upstream. It is concluded that the favourable conditions for rapid DME decomposition into soot precursors enhances soot inception while depleting the necessary species for further soot mass growth, dramatically reducing soot concentration.
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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 | 0.001 |
| 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".