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Record W3034040308 · doi:10.1002/smll.202002203

Porous Carbon Membrane‐Supported Atomically Dispersed Pyrrole‐Type FeN<sub>4</sub> as Active Sites for Electrochemical Hydrazine Oxidation Reaction

2020· article· en· W3034040308 on OpenAlexaff
Yucheng Wang, Liyang Wan, Peixin Cui, Lei Tong, Yuqi Ke, Tian Sheng, Miao Zhang, Shuhui Sun, Hai‐Wei Liang, Yuesheng Wang, Karim Zaghib, Zhi‐You Zhou, Jiayin Yuan

Bibliographic record

VenueSmall · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsInstitut National de la Recherche ScientifiqueHydro-Québec
FundersVetenskapsrådetEuropean Research CouncilNational Natural Science Foundation of China
KeywordsElectrocatalystHydrazine (antidepressant)ElectrochemistryCatalysisHeteroatomMaterials scienceMembraneCarbon fibersInorganic chemistryChemical engineeringAnodeElectrodeChemistryOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract The rational design of catalytically active sites in porous materials is essential in electrocatalysis. Herein, atomically dispersed Fe‐N x sites supported by hierarchically porous carbon membranes are designed to electrocatalyze the hydrazine oxidation reaction (HzOR), one of the key techniques in electrochemical nitrogen transformation. The high intrinsic catalytic activity of the Fe‐N x single‐atom catalyst together with the uniquely mixed micro‐/macroporous membrane support positions such an electrode among the best‐known heteroatom‐based carbon anodes for hydrazine fuel cells. Combined with advanced characterization techniques, electrochemical probe experiments, and density functional theory calculation, the pyrrole‐type FeN 4 structure is identified as the real catalytic site in HzOR.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.214
Teacher spread0.201 · 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

Citations50
Published2020
Admission routes1
Has abstractyes

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