MétaCan
Menu
Back to cohort
Record W4394840548 · doi:10.1021/accountsmr.3c00224

Recent Progress in Cathode Material Design for CO<sub>2</sub> Electrolysis: From Room Temperature to Elevated Temperatures

2024· article· en· W4394840548 on OpenAlexafffund
Peng‐Fei Sui, Min‐Rui Gao, Yicheng Wang, Jing‐Li Luo

Bibliographic record

VenueAccounts of Materials Research · 2024
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundUniversity of Alberta
KeywordsElectrolysisCathodeMaterials scienceOxideFossil fuelNanotechnologyProcess engineeringElectrolyteChemical engineeringElectrodeWaste managementMetallurgyChemistryEngineering

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Conspectus Rapid economic growth and societal development have led to an ever-increasing demand for energy; the excessive exploration and use of fossil fuels have caused an alarming level of carbon dioxide (CO 2 ) emission into the atmosphere, adversely impacting the environment and quality of life in human society. CO 2 electrolysis (CO 2 RR) offers the opportunity to store renewable energy (such as wind, solar, or tidal energy) in the form of chemicals and fuels while reducing CO 2 emissions. Through the CO 2 RR process, a variety of chemicals and fuels can be obtained using different electrocatalysts. Based on the different operating temperature and reaction conditions, CO 2 electrolysis can be categorized into low-temperature and high-temperature CO 2 RR. To date, great effort has been devoted to designing the electrocatalysts that can improve the electrocatalytic performance for CO 2 RR, including catalytic activity, selectivity, and stability. For low-temperature CO 2 RR, different approaches have been utilized to optimize the catalyst structure and properties, thereby enhancing the electrocatalytic performance. Given the different working mechanism of high-temperature CO 2 RR operating in the solid oxide electrolysis cells (SOECs), the cathode materials not only need to meet the requirements of the low temperature but also need to possess high ionic and electronic conductivity, robust coking resistance, and superior compatibility with the electrolytes. In pursuit of this objective, considerable effort is directed toward designing more efficient and effective cathode electrodes for high-temperature CO 2 RR. Beyond traditional metal and metal oxide materials, perovskite-based materials are emerging as promising candidates due to their unique structure and favorable performance in CO 2 RR at elevated temperatures. In this Account, we present recent research progress on the design of cathode materials in CO 2 electrolysis. We first discuss low-temperature CO 2 RR electrocatalyst design using different engineering strategies, including structural engineering, defect engineering, phase engineering, doping engineering, interface engineering, and microenvironment engineering. Combined with some representative work from our group and other researchers, the advantages of these diverse strategies are further elucidated, providing a more in-depth understanding of electrocatalyst design. Then, we summarize the cathode materials for high-temperature CO 2 RR utilization based on the material types such as metal/metal oxides and perovskite-based materials. Further discussion of different approaches, such as infiltration, doping, and in situ exsolution is summarized, aims to improving the electrocatalytic performance of perovskite-based materials for high-temperature CO 2 RR. Finally, we present current challenges and future prospects of CO 2 electrolysis in both the design of cathode materials and the reaction system, with the goal of achieving more profitable applications.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.035
GPT teacher head0.350
Teacher spread0.315 · 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 teacher head, not a consensus.

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

Citations24
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueAccounts of Materials ResearchSame topicCO2 Reduction Techniques and CatalystsFrench-language works237,207