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Record W4383053637 · doi:10.5281/zenodo.8111502

2022 roadmap on low temperature electrochemical CO2 reduction

2022· article· en· W4383053637 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsnot available
FundersLawrence Livermore National LaboratoryOffice of Naval ResearchTata Steel NederlandNatural Sciences and Engineering Research Council of CanadaInstitut Universitaire de FranceMinistry of Science and ICT, South KoreaTata SteelOffice of Energy EfficiencyVillum FondenNational Research Foundation of KoreaFondazione Ticino OlonaU.S. Department of EnergyNational Natural Science Foundation of ChinaNational Aeronautics and Space AdministrationCalifornia Energy CommissionDanmarks GrundforskningsfondSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungSeoul National UniversityEuropean CommissionOffice of Fossil EnergyU.S. Air ForceDeutsche ForschungsgemeinschaftNational Research FoundationNational Research Council CanadaSmall Business Technology TransferInstitute for Basic ScienceNederlandse Organisatie voor Wetenschappelijk OnderzoekTomKat Center for Sustainable Energy, Stanford UniversityAgence Nationale de la RechercheInnovationsfondenBeijing National Laboratory for Molecular SciencesOffice of Energy Efficiency and Renewable EnergyNational Science Foundation
KeywordsReduction (mathematics)ElectrochemistryEnvironmental scienceMaterials scienceChemistryMathematicsElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Electrochemical CO<sub>2</sub> reduction (CO<sub>2</sub>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<sub>2</sub>R technology: energy efficiencies, selectivities, low current densities, and stability. We highlight the opportunities in establishing rigorous standards for benchmarking performance, advances in <em>in operando</em> 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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0430.002

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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