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Record W2981982197 · doi:10.1021/acscatal.9b04214

Determination of the Evolution of Heterogeneous Single Metal Atoms and Nanoclusters under Reaction Conditions: Which Are the Working Catalytic Sites?

2019· article· en· W2981982197 on OpenAlexafffund
Lichen Liu, Debora Meira, Raúl Arenal, Patricia Concepción, Alberto V. Puga, Avelino Corma

Bibliographic record

VenueACS Catalysis · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsCanadian Light Source (Canada)
FundersH2020 European Research CouncilAgencia Estatal de InvestigaciónMinisterio de Economía y CompetitividadGobierno de AragónEuropean CommissionEuropean Regional Development FundHorizon 2020 Framework ProgrammeCanadian Light SourceEuropean Social FundU.S. Department of Energy
KeywordsCatalysisNanoclustersDehydrogenationReactivity (psychology)Heterogeneous catalysisX-ray absorption spectroscopyMetalNanoparticleNanomaterial-based catalystCharacterization (materials science)Materials scienceChemistrySubstrate (aquarium)SpectroscopyChemical engineeringAbsorption spectroscopyPhotochemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

evolution reaction. By in situ X-ray absorption spectroscopy, in situ IR spectroscopy, and high-resolution electron microscopy techniques, we will show that some characterization techniques carried out in an inadequate way can introduce confusion on the interpretation of coordination environment of highly dispersed Pt species. Finally, the combination of catalytic reactivity and in situ characterization techniques shows that, depending on the catalyst-reactant interaction and metal-support interaction, singly dispersed metal atoms can rapidly evolve into metal clusters or nanoparticles, being the working active sites for those abovementioned heterogeneous reactions.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
Teacher spread0.224 · 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

Citations286
Published2019
Admission routes2
Has abstractyes

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