A Versatile Converter of Liquid Hydrocarbons for the Production of Reducing and Carbonization Atmospheres
Bibliographic record
Abstract
Abstract We herein report the results of our investigation into the modes of catalytic partial oxidation (CPOX) of liquid fuels and air mixtures to yield endothermic (endo) gas on a pilot-scale installation containing ~ 0.45 cm 3 catalytic bed. This endothermic gas serves as a protective atmosphere in thermochemical steel treatment processes. Seven liquid hydrocarbons (LHs) are investigated, namely isooctane, 91 RON (research octane number) and 95 RON gasoline, diesel, kerosene, jet fuel, and naphtha. All experiments are performed using our previously developed reactor, where the reactions of natural gas/air mixtures were previously studied. In the present study, we report that the LH conversion products reached an equilibrium state similar to that of methane and natural gas conversion with an atomic C/O ratio of ~ 1.0 in the mixture. Furthermore, working regimes between 850 and 950 °C are examined as typical reaction conditions for industrial endo gas generators, and in all cases, the required gas quality is achieved. However, we found that gasoline and diesel are the most suitable LH feedstock for endo gas generation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".