Dry‐Reforming of Ethanol in the Presence of a 316 Stainless Steel Catalyst
Bibliographic record
Abstract
Abstract Dry‐reforming is a known process for the production of synthetic gas from natural gas or other volatile fossil fuels. Another possible application is the reforming of hydrocarbons contained in the synthetic gas produced from biomass or waste gasification. The absence of wide industrial process applications is mainly due to the high endothermicity of the reactions involved and technical problems associated with carbon formation. In this work, the target reaction is: The principal challenge is that of using a 2D catalyst formulation favouring the target reaction and permitting easy retrieval of deposited carbon while, at the same time, preserving the catalyst's activity and structural integrity. This paper presents the results obtained from the use of a 316 stainless steel catalyst. The catalyst is active in ethanol dry reforming as the yield of hydrogen reached 98% of the theoretical value. Moreover, the co‐product carbon is of a filamentous form and can be easily retrieved without risk of modification to the catalyst properties. This catalyst is recyclable; it can be used several times over in the dry‐reforming of ethanol process without detectable change in its activity and selectivity.
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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".