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). Using Aspen Plus, a direct air carbon capture process is modelled in tandem with SOEC to generate carbon monoxide and hydrogen, which are subsequently converted to fuels. The carbon capture model uses regenerative loops of sodium hydroxide and sodium carbonate as well as calcium hydroxide and calcium carbonate to selectively remove the dilute carbon dioxide from the air. Other than filtered air, the only other output of this process is a stream of gaseous water and carbon dioxide at an elevated temperature, which is fed to a SOEC stack. The SOEC model assumes that carbon dioxide is converted to carbon monoxide by the reverse water gas shift reaction and water is converted to hydrogen and oxygen through electrolysis. The different components of the SOEC and their inherent flows of materials and heat are simulated using unit operations available in Aspen Plus. The gas mixture from the SOEC (mixture of H2/CO/CO2/H2O) is further transformed into profitable fuels such as methane and methanol, whose respective processes are also simulated in Aspen Plus. Clean electricity sources are considered for the model and energy requirements are minimized through process synthesis; for example, there exists some good synergies between the direct air capture process and the SOEC to minimize the energy necessary to bring the SOEC feed to its operating temperature of ca. 800°C. Sensitivity analysis are performed on the entire process (direct air capture/SOEC/fuel synthesis) to reveal the effect of key operating parameters (e.g. conversion inside the SOEC, composition of SOEC inlet) on the production of fuels or amount of electricity requirement per amount of fuel produced.
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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".