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Record W4388823715 · doi:10.1021/jacs.3c08930

Oxygen-Resistant CO <sub>2</sub> Reduction Enabled by Electrolysis of Liquid Feedstocks

2023· article· en· W4388823715 on OpenAlexafffund
Douglas J. D. Pimlott, Andrew Jewlal, Yongwook Kim, Curtis P. Berlinguette

Bibliographic record

VenueJournal of the American Chemical Society · 2023
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of British Columbia
FundersCanada First Research Excellence FundCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanadian Institute for Advanced Research
KeywordsChemistryElectrolysisBicarbonateCathodeRaw materialAqueous solutionElectrolyteSolubilityInorganic chemistryOxygenOxygenateChemical engineeringCatalysisElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Electrolytic CO 2 reduction fails in the presence of O 2 . This failure occurs because the reduction of O 2 is thermodynamically favored over the reduction of CO 2 . Consequently, O 2 must be removed from the CO 2 feed prior to entering an electrolyzer, which is expensive. Here, we show that the use of liquid bicarbonate feedstocks (e.g., aqueous 3.0 M KHCO 3 ), rather than gaseous CO 2 feedstocks, enables efficient and selective CO 2 reduction without additional procedures for removing O 2 . This effect is made possible because liquid bicarbonate solutions, which serve as a liquid CO 2 carrier, deliver high concentrations of captured CO 2 to the cathode, while the low solubility of O 2 in aqueous media maintains a low O 2 concentration at the same cathode surface. Consequently, electrolyzers fed with liquid bicarbonate feedstocks create an environment at the cathode that favors the reduction of CO 2 over O 2 . We validate this claim by electrochemically converting CO 2 into CO with reaction selectivities of 65% at 100 mA cm –2 using a 3.0 M KHCO 3 solution bubbled with 100% CO 2 or 100% O 2 . Similar experiments performed with a gaseous CO 2 feedstock showed that merely 0.5% of O 2 in the feedstock reduced CO selectivity by >90% after 1 h of electrolysis. Our findings demonstrate that a liquid bicarbonate feedstock enables efficient CO 2 reduction without the need for expensive O 2 removal steps.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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

Citations55
Published2023
Admission routes2
Has abstractyes

Explore more

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