Production of Carbon Neutral Methanol Using Co-Electrolysis of CO<sub>2</sub> and Steam in Solid Oxide Electrolysis Cell in Tandem with Direct Air Capture
Bibliographic record
Abstract
The increasing concentration of carbon dioxide (CO2) in the atmosphere since the industrial revolution is a major contributor to climate change. Among the several options to tackle this issue, the removal of CO2 from the atmosphere and its subsequent use is becoming increasingly attractive. This paper presents a techno-economic feasibility study and quantification of the environmental benefits of combining direct air capture (i.e. capturing CO2 from the atmosphere) with co-electrolysis of water and the captured CO2 in a solid oxide electrolyser cell (SOEC). It was found that the fuel methanol could be modelled to be produced in a carbon negative manner but is not profitable due to current SOEC capital cost. The capital cost of the SOEC is expected to be cut in half by 2030. This would allow for profitable production of methanol.
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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".