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Record W2331124854 · doi:10.1021/jp4035858

Structure and Properties of Small Aurocarbons: A Selective Study

2013· article· en· W2331124854 on OpenAlexafffund
C. N. Ramachandran, Fedor Y. Naumkin

Bibliographic record

VenueThe Journal of Physical Chemistry A · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ontario Institute of Technology
KeywordsCarbon fibersChemical physicsIonization energyElectron affinity (data page)Density functional theoryElectronic structureMaterials scienceDopantHydrocarbonIonizationChemistryComputational chemistryMoleculeDopingOrganic chemistryIon

Abstract

fetched live from OpenAlex

Gold clusters are versatile catalysts, and adding nonmetal dopants can allow tuning of their electronic properties via both shape and composition alteration. In the present work, mixed clusters of carbon and gold atoms are studied in terms of structure, stability, and the correlation between the shape and electronic properties by using a density functional theory approach. Four series of isomers (hydrocarbon analogues, carbon chains and cycles on gold surface, and carbon cores encapsulated by gold atoms) are investigated, exhibiting variation of the relative stability with the system size. Calculated vertical ionization energies, vertical electron affinities, and HOMO-LUMO energy gaps of the mixed clusters show a considerable change relative to the values for the pure gold clusters, the properties generally altering more strongly for the gold-encapsulated-carbon isomers. Also discussed are the structure, stability, and properties of larger clusters with a few such encapsulated-carbon units, with pronounced effects due to aggregation.

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 score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.226
Teacher spread0.215 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry ASame topicCatalytic Processes in Materials ScienceFrench-language works237,207