The engine reformer: Syngas production in an engine for compact gas‐to‐liquids synthesis
Bibliographic record
Abstract
Methane (CH4) reforming was carried out in an internal combustion engine (an “engine reformer”). We successfully produced syngas from the partial oxidation of natural gas in the cylinder of a diesel engine that was reconfigured to perform spark ignition. Performing the reaction in an engine cylinder allows some of the exothermicity to be captured as useful work. Intake conditions of 110 kPa and up to 480 °C allowed low cycle‐to‐cycle variability (COVnimep < 20 %) at methane‐air equivalence ratios (ϕM) of 2.0, producing syngas with an H2‐to‐CO ratio of 1.4. Spark ignition timing was varied between 45–30° before top‐dead‐center (BTDC) piston position, showing significant improvement with delayed timing. Hydrogen (H2) and ethane (C2H6) were added to simulate recycle from a downstream synthesis reactor and realistic natural gas compositions, respectively. Adding these gases yielded a stable combustion up to hydrocarbon‐air equivalence ratios (ϕHC) of 2.8 with COVnimep < 5 %. Ethane concentrations (with respect to methane) of up to 0.2 L/L (20 vol%) (with and without H2) produced robust and stable combustions, demonstrating that the engine can be operated across a range of natural gas compositions. Engine exhaust soot concentrations demonstrated elevated values at ϕHC > 2.4, but < 1 mg/L below these equivalence ratios. These results demonstrate that the engine reformer could be a key component of a compact gas‐to‐liquids synthesis plant by highlighting the operating conditions under which high gas conversion, high H2‐to‐CO ratios close to 2.0, and low soot production are possible.
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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".