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Record W4410055713 · doi:10.1016/j.jcou.2025.103096

Integrated direct air CO2 capture and solid oxide electrolyzer for sustainable chemical production: Case studies of methanol and synthesis fuel

2025· article· en· W4410055713 on OpenAlexafffundabout
Mohammad Ali Emadi, Vahid Barahimi, Eric Croiset

Bibliographic record

VenueJournal of CO2 Utilization · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaEnvironment and Climate Change Canada
KeywordsElectrolysisSustainable productionMethanolProduction (economics)Environmental scienceOxideProcess engineeringWaste managementMaterials scienceChemical engineeringChemistryEngineeringMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

This paper presents a comprehensive study of a novel system aimed at producing chemicals from CO 2 captured from the atmosphere by integrating direct air capture (DAC) and solid oxide electrolysis cell (SOEC). Two case studies for the chemical produced were considered: CO 2 to methanol and CO 2 to synthetic fuel (synfuel). All scenarios were based on a DAC system capturing 250,000 tonnes per year of CO 2 from the atmosphere. Using Aspen Plus, the results revealed insights into energy consumption, resource utilization, and economic viability. The system produced 36.4 tonne/hr of methanol and 15.1 tonne/hr of synfuel. Methanol production requires 403 MW of electricity and 10.9 tonne/hr of natural gas, with a specific energy consumption of 26.0 kWh/kg-MeOH. Synfuel production demands higher utility usage of 53.9 kWh/kg-synfuel (360 MW electricity, and 7.09 tonne/hr of natural gas). Economic analysis shows a total annual cost and levelized production cost for methanol of $346 M/year and 1.32 $/kg, respectively; for synfuels, the values are $301 M/year and 2.78 $/kg, respectively. Environmental analysis indicates that the amount of CO 2 captured per product unit is for synfuel 1.88 kg-CO 2 captured/kg-synfuel, and for methanol 0.58 kg-CO 2 captured/kg-MeOH. Using Ontario's grid and natural gas emission factor, emission for methanol production amounts to 31.1 g-CO 2 -eq/MJ-MeOH, while for synfuel, it stands at 5.2 g-CO 2 -eq/MJ-synfuel. However, these emissions can be notably reduced by transitioning to renewable sources of electricity and can even become negative in the case of synfuel when hydropower and wind are used as electricity sources. • A CO 2 direct air capture/SOEC to methanol or synfuel system is proposed. • The system is based on a 250,000 tonne/year of CO 2 captured by DAC. • The system produces 36.4 tonne/hr of methanol and 15.1 tonne/hr of synfuel. • Levelized production costs are 1.32 $/kg MeOH and 2.78 $/kg Synfuel . • Equivalent GHG emissions are 31.1 g CO 2 -eq/MJ-MeOH and 5.2 g CO 2 -eq/MJ-synfuel

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.296
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2025
Admission routes3
Has abstractyes

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