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Record W4405642336 · doi:10.1002/cssc.202482404

Cover Feature: Electrocatalysts for Urea Synthesis from CO<sub>2</sub> and Nitrogenous Species: From CO<sub>2</sub> and N<sub>2</sub>/NOx Reduction to urea synthesis (ChemSusChem 24/2024)

2024· article· en· W4405642336 on OpenAlexaff
Li Chun, Qiuji Zhu, Chaojie Song, Yimin Zeng, Ying Zheng

Bibliographic record

VenueChemSusChem · 2024
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsBC Innovation CouncilNational Research Council CanadaWestern University
Fundersnot available
KeywordsUreaNOxCover (algebra)Reduction (mathematics)ChemistryInorganic chemistryEnvironmental chemistryMaterials scienceOrganic chemistryCombustionEngineering

Abstract

fetched live from OpenAlex

The Cover Feature highlights the innovative potential of electrocatalytic C−N coupling for direct urea synthesis under ambient conditions, offering a sustainable alternative to the traditional energy-intensive Haber–Bosch process. By using carbon dioxide and nitrogenous species, this approach eliminates the need for ammonia production. In their Review, Y. Zeng, Y. Zheng and co-workers discuss the role of intermediates, active sites, and catalyst design strategies that enhance urea production, emphasizing the mechanistic insights and challenges that will shape future advancements in this field. Detailed exploration of these aspects aims to inspire further development of efficient electrocatalysts for sustainable urea synthesis.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
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 score0.037
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.219
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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