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Record W4282838394 · doi:10.1088/2515-7655/ac7823

2022 roadmap on low temperature electrochemical CO<sub>2</sub> reduction

2022· article· en· W4282838394 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

VenueJournal of Physics Energy · 2022
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of TorontoNational Research Council Canada
FundersLawrence Livermore National LaboratoryOffice of Naval ResearchTata Steel NederlandNatural Sciences and Engineering Research Council of CanadaFondazione Ticino OlonaMaterials innovation instituteTata SteelOffice of Energy EfficiencyVillum FondenNational Research Foundation of KoreaU.S. Department of EnergyNational Natural Science Foundation of ChinaXi’an Jiaotong UniversityNational Aeronautics and Space AdministrationCalifornia Energy CommissionDanmarks GrundforskningsfondSeoul National UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungInstitute for Basic ScienceNederlandse Organisatie voor Wetenschappelijk OnderzoekConsejo Nacional de Ciencia y TecnologíaTomKat Center for Sustainable Energy, Stanford UniversityAgence Nationale de la RechercheOffice of Fossil EnergyEuropean CommissionU.S. Air ForceDeutsche ForschungsgemeinschaftNational Research FoundationNational Research Council CanadaSmall Business Technology TransferBeijing National Laboratory for Molecular SciencesLaboratory Directed Research and DevelopmentOffice of Energy Efficiency and Renewable EnergyNational Science FoundationImperial College LondonInnovationsfondenMinistry of Science and ICT, South KoreaInstitut Universitaire de France
KeywordsReduction (mathematics)ElectrochemistryMaterials scienceEnvironmental scienceChemistryElectrodeMathematicsPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Electrochemical CO 2 reduction (CO 2 R) is an attractive option for storing renewable electricity and for the sustainable production of valuable chemicals and fuels. In this roadmap, we review recent progress in fundamental understanding, catalyst development, and in engineering and scale-up. We discuss the outstanding challenges towards commercialization of electrochemical CO 2 R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in in operando characterization, the discovery of new materials towards high value products, the investigation of phenomena across multiple-length scales and the application of data science towards doing so. We hope that this collective perspective sparks new research activities that ultimately bring us a step closer towards establishing a low- or zero-emission carbon cycle.

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 score0.034
Threshold uncertainty score0.760

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 integrity0.0000.001
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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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