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Record W3199065770 · doi:10.1021/acsenergylett.1c01639

Glycerol Oxidation Pairs with Carbon Monoxide Reduction for Low-Voltage Generation of C<sub>2</sub> and C<sub>3</sub> Product Streams

2021· article· en· W3199065770 on OpenAlexafffund
Hossein Yadegari, Adnan Ozden, Tartela Alkayyali, Vikram Soni, Arnaud Thevenon, Alonso Rosas‐Hernández, Theodor Agapie, Jonas C. Peters, Edward H. Sargent, David Sinton

Bibliographic record

VenueACS Energy Letters · 2021
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaOffice of ScienceHorizon 2020 Framework ProgrammeCanadian Institute for Advanced ResearchOntario Research FoundationU.S. Department of Energy
KeywordsAnodeCarbon monoxideElectrochemistryCarbon fibersChemistryOxygen evolutionElectrochemical reduction of carbon dioxideRenewable energyChemical engineeringInorganic chemistryMaterials scienceElectrodeCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Electrochemical carbon dioxide reduction to multicarbon products provides the storage of renewable energy in the form of chemical bonds, as well as a means to displace fossil sources of chemical feedstocks. However, the accompanying anodic oxygen evolution reaction (OER) reduces the energy efficiency of the process without providing a salable product. Replacing OER with alternative organic oxidation reactions (OORs) is an emerging strategy to reduce the full-cell potential and generate valuable products on both sides of the cell. We pursue carbon monoxide reduction that avoids carbonate formation and benefits from highly alkaline anode conditions favorable for OOR. This coelectrolysis strategy achieves a cathodic C 2+ product stream (71% FE) and an anodic C 3 product stream (75% FE) at 180 mA cm –2 with a full-cell potential of 1.34 V. The integrated system reduces the CO-to-C 2 H 4 energy requirement by 55% (to ∼72 GJ/ton_C 2 H 4 ), halving the projected energy cost of ethylene production from CO 2 .

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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

Citations86
Published2021
Admission routes2
Has abstractyes

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Same venueACS Energy LettersSame topicCO2 Reduction Techniques and CatalystsFrench-language works237,207