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Record W4238826299 · doi:10.1002/ange.201703301

Nitrogen Photofixation over III‐Nitride Nanowires Assisted by Ruthenium Clusters of Low Atomicity

2017· article· en· W4238826299 on OpenAlexafffund
Lu Li, Yichen Wang, Srinivas Vanka, Xiaoyue Mu, Zetian Mi, Chao‐Jun Li

Bibliographic record

VenueAngewandte Chemie · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsMcGill UniversityCentre in Green Chemistry and Catalysis
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsNanoclustersRutheniumNitrideMaterials scienceCatalysisPhotocatalysisAtomicitySemiconductorPhotochemistryNanowireGraphitic carbon nitrideChemical engineeringNanotechnologyInorganic chemistryChemistryOptoelectronics

Abstract

fetched live from OpenAlex

Abstract In many heterogeneous catalysts, the interaction of supported metal species with a matrix can alter the electronic and morphological properties of the metal and manipulate its catalytic properties. III‐nitride semiconductors have a unique ability to stabilize ultra‐small ruthenium (Ru) clusters (ca. 0.8 nm) at a high loading density up to 5 wt %. n‐Type III‐nitride nanowires decorated with Ru sub‐nanoclusters offer controlled surface charge properties and exhibit superior UV‐ and visible‐light photocatalytic activity for ammonia synthesis at ambient temperature. A metal/semiconductor interfacial Schottky junction with a 0.94 eV barrier height can greatly facilitate photogenerated electron transfer from III‐nitrides to Ru, rendering Ru an electron sink that promotes N≡N bond cleavage, and thereby achieving low‐temperature ammonia 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)0.000
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 score0.002
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.239
Teacher spread0.226 · 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

Citations28
Published2017
Admission routes2
Has abstractyes

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