MétaCan
Menu
Back to cohort
Record W4392462478 · doi:10.1016/j.coelec.2024.101468

The rebirth of urea oxidation reaction for power-to-X and beyond

2024· article· en· W4392462478 on OpenAlexfundno aff
Joudi Dabboussi, Rüdiger‐A. Eichel, Hans Kungl, Rawa Abdallah, Gabriel Loget

Bibliographic record

VenueCurrent Opinion in Electrochemistry · 2024
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory HealthCentre National de la Recherche Scientifique
KeywordsUreaChemistryPower (physics)RedoxMaterials scienceNanotechnologyInorganic chemistryOrganic chemistryPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Despite the longstanding interest in urea oxidation reaction (UOR), the identification of reaction products under conventional conditions was only reported recently. It turns out that the initially thought “sustainable pathway”, leading to harmless products, represents just a small fraction of the overall reaction mechanism. This is detrimental as the use of urea-rich aqueous feeds for H2 production, along with their remediation through UOR, constitutes perhaps the most important added value of this process for power-to-X and clinical applications. Nonetheless, promising strategies favoring the formation of environmentally friendly products over harmful overoxidized ones already exist. This is expected to lead to a “rebirth” of this research field and open the quest for ultimate selectivity to ensure the complete sustainability of UOR. Therefore, the systematic analysis of reaction products, the elucidation of mechanisms for improving N2 faradaic efficiency, and the design of selective catalysts should be the next focus of research in the field of UOR.

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)0.000
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 score0.015
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.015
GPT teacher head0.324
Teacher spread0.309 · 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.

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

Citations6
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Opinion in ElectrochemistrySame topicCatalytic Processes in Materials ScienceFrench-language works237,207