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Record W2950756683 · doi:10.1002/cctc.201900910

Homogenous Meets Heterogenous and Electro‐Catalysis: Iron‐Nitrogen Molecular Complexes within Carbon Materials for Catalytic Applications

2019· article· en· W2950756683 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemCatChem · 2019
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMcGill UniversityCentre in Green Chemistry and Catalysis
FundersEngineering and Physical Sciences Research Council
KeywordsCatalysisElectrocatalystNanotechnologyCarbon fibersChemistryElectrochemistryRedoxReactivity (psychology)Materials scienceCombinatorial chemistryInorganic chemistryOrganic chemistryElectrodePhysical chemistryComposite number

Abstract

fetched live from OpenAlex

Abstract High activity, selectivity and recyclability are crucial parameters in the design of performant catalysts. Furthermore, depletion of platinum‐group metals (PGM) drives further research towards highly available metal‐based catalysts. In this framework, iron‐based active sites supported on nitrogen‐doped carbon materials (Fe/N@C) have been explored to tackle important applications in organic chemistry, for both oxidation and reduction of C−O/C−N bonds, as well as in electrocatalysis for energy applications. This versatile reactivity makes them ideal substitutes to PGM‐based catalysts, being based on abundant elements. Despite important advances in material science and characterisation techniques allowing the analysis of heterogeneous/electro‐ catalysts at the atomic scale, the nature of the catalytically active sites in Fe/N@C remains elusive. Most recent theoretical studies point at individual FeN x single sites as the origin of the catalytic activity. Although their identification is still challenging with current technology, establishing their real nature will foster further research on these PGM‐free and redox‐polyvalent catalysts. In this review, we provide an overview of their applications in both thermal and electrochemical processes. Throughout the review, we highlight the different characterisation techniques employed to gain insight into the catalyst's active sites.

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 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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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