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Record W3034743260 · doi:10.1021/acsenergylett.0c00898

Electrodes Designed for Converting Bicarbonate into CO

2020· article· en· W3034743260 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Energy Letters · 2020
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsCanadian Institute for Advanced ResearchUniversity of British Columbia
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada First Research Excellence FundCanada Foundation for InnovationUniversity of British ColumbiaCanadian Institute for Advanced Research
KeywordsElectrolyteGas diffusion electrodeCarbon fibersChemical engineeringAqueous solutionGaseous diffusionBicarbonateElectrodeMaterials scienceChemistryProcess engineeringNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

The deployment of electrolyzers that convert CO2 into chemicals and fuels requires appropriate integration with upstream carbon capture processes. To this end, the electrolytic conversion of aqueous (bi)carbonate offers the opportunity to avoid the energy-intensive steps currently used to extract pressurized CO2 from carbon capture solutions. We demonstrate here that an optimized silver gas diffusion electrode (GDE) architecture enables conversion of model carbon capture solutions (i.e., 3 M KHCO3) into CO at partial current densities (JCO) greater than 100 mA cm–2 with CO2 utilization rates of ∼70%. These results exceed the performance of any previously reported liquid-fed CO2 electrolyzers and rival gas-fed devices. We were able to hit these metrics through the systematic design of gas diffusion layer (GDL) components (e.g., polytetrafluoroethylene) and catalyst layer constituents (i.e., Nafion, silver) on CO production. A key finding of this work is that hydrophobic GDE components (which are common to gas-fed CO2RR electrolyzers) decrease in situ CO2 generation and thus the formation of the final CO product. These findings show a clear path toward industrially relevant reactors that couple electrolytic CO2 conversion with carbon capture.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.195
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.240
Teacher spread0.225 · 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