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Record W2794332351 · doi:10.1002/cctc.201701958

Surface/Interfacial Catalysis of (Metal)/Oxide System: Structure and Performance Control

2018· article· en· W2794332351 on OpenAlexaff
Weijie Ji, Chak‐Tong Au

Bibliographic record

VenueChemCatChem · 2018
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsOxideCatalysisMetalMaterials scienceNanotechnologyParticle (ecology)Surface (topology)Complex oxideMetal particleChemical engineeringNanoparticleChemistryMetallurgyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Surface/interfacial catalysis on a series of oxide substrates and metal/oxide interfaces has been reviewed. Special attention has been paid to those systems in which the oxide substrates are structurally defined with certain exposed facets, and the metal assembling is well controlled with desired particle size and narrow particle size distribution. The distinct catalytic behaviors over the selected systems have been discussed in line with their specific surface/interfacial structure features as well as other surface properties. The tactics and cations how to build up the novel metal/oxide interfacial structures are provided, and the guideline for extended reaction exploration is also suggested. Success in structure and performance control on these important systems is highly valuable for designing more selective and efficient catalyst in practical applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.008
GPT teacher head0.222
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations39
Published2018
Admission routes1
Has abstractyes

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